Quantitative Analysis of Cell-Surface
Interactions and Cell Adhesion Process
in Real-time
A Thesis
Submitted to the Faculty
of
Drexel University
by
Soonjin Hong
in partial fulfillment of the
requirements for the degree of
Doctor of Philosophy
April 2008
© Copyright 2008
Soonjin Hong. All Rights Reserved
I
ACKNOWLEDGEMENTS
I would like to express my gratitude to many people for the precious and
continuous help and guidance. Without them, I would not be able to accomplish my
Ph.D.
First of all, I'd like to thank to my adviser, Dr. Kenneth A. Barbee. His
knowledgeable advice and suggestion guided me to fruitful results and made it
possible to do the comprehensive research. I was able to learn how to plan and
conduct the in-depth research, which will be a great asset to my future career.
Especially, I thank him for his humane attitude to understand a student’s situation.
I am also very grateful to committee members, Drs. Lec, Allen, Marcolongo and
Reginato, for their technical and academic advice. Their comments and feedbacks
were valuable in refining the thesis. Dr. Lec gave me continuous advice on the sensor
system. Dr. Marcolongo kindly allowed me to use her experimental apparatus and Dr.
Reginato generously provided me with cells and valuable suggestions on the
experiments.
I appreciate to all my friends in Dr. Barbee’s and Dr. Lec’s lab and I would like to
remind the friendship with Dihui Hong, Devrim Kilinc, Allison Andrews, Ertan
Ergezen, Robert Hart and Dr. Dianne Rothstein. Lastly, I would like to give my
special thanks to my wife and children; Kyungcho, Alex, Hannah, Andrew and Emily.
II
TABLE OF CONTENTS
LIST OF TABLES
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III
LIST OF FIGURES
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IV
ABSTRACT
CHAPTER 1
---------------------------------------------------------------------------------------------BACKGROUND
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1.1 Cell adhesion mediated by complex intracellular and extracellular events
1.2 Multi-functional integrin and intrinsic adhesivity of cells
1
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1
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3
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4
1.5 The measurement of intrinsic adhesivity and cell spreading process
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6
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7
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7
1.6 Thickness Shear Mode resonator
1.7 Objectives
1
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1.3 Cell spreading determined by integrin bindings and actin filament dynamics
1.4 The phenotype of oncogene expressing cells
VII
CHAPTER 2
CELL-SURFACE ADHESIVE INTERACTIONS
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11
2.1 Introduction
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11
2.2 Material and methods
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12
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15
2.4 Discussion
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17
CHAPTER 3
INTRINSIC ADHESIVITY AND CELL SPREADING
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31
3.1 Introduction
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31
2.3 Results
3.2 Material and methods
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32
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35
3.4 Discussion
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37
CHAPTER 4
CELL STIFFNESS AND DEFORMABILITY
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51
4.1 Introduction
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51
3.3 Results
4.2 Material and methods
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53
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55
4.4 Discussion
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56
CHAPTER 5
CONCLUSION AND FUTURE WORK
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66
5.1 Conclusions
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66
5.2 Future work
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67
4.3 Results
LIST OF REFERENCES
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69
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75
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86
APPENDIX
VITA
III
LIST OF TABLES
Table 2.1 Evaluation of cell adhesion and its kinetics ............................................................................. 30
Table 3.1 Three phases of cell spreading process..................................................................................... 50
IV
LIST OF FIGURES
Figure 1.1 The mechanism of the operation of TSM sensor and TSM sensor responses in network analyzer
(B). By the piezoelectric effect, TSM sensor laterally vibrates according to the applied voltage and
this vibration is affected by the mechanical properties, such as density and viscosity, of the
interface that is very close to the sensor surface. Thus, the cell adhesion process, accompanying
mechanical property changes, can be reported by the sensor readings. ................................................. 10
Figure 2.1 Time course of
R due to the adhesion process of endothelial cells for the initial adhesion (A) and
the steady state adhesion (B). Cell adhesion process can be characterized by changes in the delay
time, the slope of the initial decrease, and the size of
R at plateaus. .................................................. 22
Figure 2.2 Correlation of sensor readings with optical observation. The cell suspensions in serum-free media
were placed on bare and gelatin coated TSM sensors in the incubator (37ºC, 5% CO2). The area
of sensor surface and the number of cells were 0.95 cm2 and 150×103. The sensor readings (△R)
were recorded for 1 hrs (A). For the optical observation, TSM sensors were rinsed with PBS at
various time points during the incubation and adherent cells were counted with the fluorescent
microscope. Optical data are presented with SD. N=5 (B). The correlations of △R with the
number of adherent cells were shown in (C). ......................................................................................... 24
Figure 2.3 Comparison of the number and morphology of adherent cells on bare and gelatin TSM sensor after
being rinsed with PBS at various time points. The adherent cells were visualized with
epifluorescent microscopy. Size of each picture is 800μm×600μm ...................................................... 25
Figure 2.4 Influence of integrin binding inhibition with soluble RGD on cell adhesion process. Soluble RGD
peptides (2 mM) were used for blocking integrin binding in order to inhibit the cell adhesion.
RGD treated cell suspension in serum-free media was place on gelatin coated TSM sensors at the
same time with control. The sensor readings (△R) of initial and steady state cell adhesion process
were shown in (A) and (B) respectively. ................................................................................................ 26
Figure 2.5 Comparison of adherent cells of RGD treated with control at 2 hrs and 20 hrs. TSM sensor
surfaces were rinsed with PBS at each time point and stained: A) Control, 1 hr, B) Control, 20 hr,
C) RGD treated cells, 1 hr, D) RGD treated cells, 20 hr. Size of each picture is 630 μm × 470 μm .... 27
Figure 2.6 Influence of the positively charged surface on cell adhesion process. The TSM sensor surface was
coated with positively charged PDL. The sensor readings (△R) of initial and steady state cell
adhesion process were shown in (A) and (B) respectively. ................................................................... 28
Figure 2.7 Influence of removal of HSPGs from the cell membrane on steady state cell adhesion process. The
monolayer of endothelial cells was treated with Heparinase III, digesting the significant portion of
HSPG from the cell surface..................................................................................................................... 29
Figure 3.1 MCF-10A cells overexpressing ErbB2 (NeuT) up-regulate integrin α5 expression. Lysates from
cells expressing vector alone (pBabe) or ErbB2 (pBabe-NeuT) were collected and proteins were
analyzed by immunoblotting with antibodies to ErbB2, integrin α5 and actin. .................................... 41
V
Figure 3.2 Real time phase contrast photomicrographs of MCF-10A cell spreading on FN surface. The
suspended cells (GRGDS, control and NeuT) were allowed to adhere on FN in serum free media.
Even though GRGDS cells spread slower than control cells, they showed the similar morphology.
NeuT cells showed distinct cell spreading behavior to the rest. While GRGDS and control cells
kept their spreading gradually from the round shape, NeuT cells were quite well attached and
showed fast spreading with well developed lamellipodia through out the spreading process. The
size of each photo is 600×450μm2. Enlarged photos of control and NeuT cells at 15 min
incubation were shown in D and E respectively..................................................................................... 42
Figure 3.3 A: The comparison of ΔR and ΔA during the MCF-10A cell spreading on FN surface. The
spreading area (NeuT cells: ■, Control cells: ♦, GRGDS-treated control cells: ▲), calculated from
the image processing, were depicted along with the TSM sensor response (Solid lines). This
comparison clear demonstrates that ΔR represents the real time spreading process. A significant
difference between ΔA and ΔR was observed in the early spreading of GRGDS cells, which is due
to the overestimation of real contact area. B: Long-term time course of ΔR due to the MCF-10A
cell adhesion on FN surface. NeuT cells have rapid ΔR increase to the maximum in 2 hours,
which may indicate the completion of spreading. There is no progressive increase in ΔR, and even
a slight decease, suggesting no further development of cytoskeletal structure or focal adhesions. In
contrast, normal cells have less rapid spreading response, but ΔR continued to increase after cells
are fully spread. ....................................................................................................................................... 44
Figure 3.4 Correlation of the spread area and TSM sensor reading (ΔR) for GRGDS cells(♦), control cells(■),
NeuT cells(▲). The correlation demonstrates that the cell spreading process consists of three
distinct phases. Phase I represents the initial attachment from sedimentation to flattening and the
further spreading is in phase II, which is characterized by the linear relationship between ΔR and
ΔA. The curve fitted lines from the points in this region have similar slopes and different ΔR axisintercepts (ΔRo). When the cell spreading turns into phase III, the linear relationship does not
persist. The error bar represents standard deviation (n=12) ................................................................... 45
Figure 3.5 Photomicrographs of remaining NeuT cells on the substrate after spinning disk detachment. The
distance at which 50% of adherent cells were removed was determined from these sequential
images and the corresponding shear stress (τ50%) was calculated from their linear relationship.
Since hydrodynamic force was designed to remove cells in the stage of very initial attachment.
τ50% indicates the intrinsic adhesivity of the cell. The numbers indicate the distance from the
center of the round substrate. The size of each photo is 600×450μm2. ................................................. 46
Figure 3.6 Correlation of τ50% with the initial slope of ΔR. The initial increasing slope of ΔR was calculated
from the difference of ΔR values at 5 and 10min, which is the similar time frame with the
spinning disk detachment assay for τ50%. The result demonstrates that the initial slope is linearly
proportional to τ50%. ................................................................................................................................. 47
Figure 3.7 The characteristic sensor response to the attachment and spreading may reflects differences in
adhesive properties relevant to the functional phenotype. A) MCF10A pBabe-NeuT cells have
VI
rapid spreading with large ΔR, indicating greater adhesion strength on FN. Normal cells have less
rapid spreading response, but ΔR continued the gradual increase. α5 integrin knock-down NeuT
cells showed the same profile of NeuT cells, but has reduced size of ΔR. B) The time course of
ΔR of NeuT cells on matrigel surface is similar to that of untreated controls. C) MDA-MB-231
cells followed the same profiles on both FN and matrigel surface. ....................................................... 49
Figure 4.1 A polystyrene hemisphere was attached at the end of a silicone nitride cantilever. A spherical
polystyrene bead was half melted on a flat glass slide and the AFM cantilever was engaged on the
top of the formed hemisphere with UV glue, followed by the UV light cure. The spring constant
was determined to be 0.1828N/m using a commercial calibration probe. The bar is 40µm. ................ 59
Figure 4.2 The deformation of one half of a spherical solid compressed by a rigid plate. Hertz contact theory
describes the relationship between the compressive force (F), deformation (d), and elastic modulus
(Young’s modulus) as shown in eq. (4.3). The compressive force is the function of the
deformation with the power 3/2. ............................................................................................................. 60
Figure 4.3 Axisymmetric FE model and its deformation under the compression by two rigid parallel plate.
The average Young’s modulus calculated from the Hertz contact model was assigned to FE model
and the reaction forces acting on the rigid surface wre obtained in terms of the displacement of the
rigid surface. ............................................................................................................................................ 61
Figure 4.4 Comparison of Young’s moduli calculated with Hertz contact theory (■: Control cells, ◆: CD
treated cells and ▲: NeuT overexpressing cells). For better understanding, several representative
points from 2% to 10% of cell deformation were selected for depicting the Young’s modulus.
Control cells showed bigger averaged values than NeuT cells and while NeuT and CD treated
cells maintained relatively constant values according to the deformation, those of control cells
gradually increase. Error bar indicates the standard deviation (n=10)................................................... 62
Figure 4.5 The relationship between the compressive force and the cell deformation from the experiments
(filled symbols and solid lines) and FE model simulations (hollow symbols for solid model and
◆ for Mooney-Rivlin solid model). Representative force curves were shown in the inset. Error
bar indicates the standard deviation (n=10). ........................................................................................... 63
Figure 4.6 Stress and strain curves of the elastic solid model (solid line) and MR hyperelastic solid model
(dashed line). While solid model has linear stress-strain curve (δ-ε), MR hyperelastic solid model
showed non-linear relationship. .............................................................................................................. 64
Figure 4.7 The influence of the cell stiffness on the initial attachment of cells. The adhesion of control cells
showed the typical time course of ΔR, but that of CD treated cell showed slightly higher values in
the initial stage (<2.5min), noted by ▼, and gradually increased. This may indicate that CD
treated cells deform faster and generate greater sensor signals than control cells................................. 65
VII
ABSTRACT
Quantitative Analysis of Cell-Surface Interactions and Cell Adhesion Process in Real-time
Soonjin Hong
Kenneth A. Barbee, Ph.D.
The cell adhesion process and cellular interactions with extracellular matrix (ECM) proteins were
quantitatively evaluated using a thickness shear mode (TSM) sensor. For understanding cell-surface
interactions, specific effects of receptor-mediated adhesion, the glycocalyx, and surface charge on
initial cell-surface attachment and steady state adhesion of bovine aortic endothelial cells (BAECs)
were investigated. The result showed that integrin binding determines the kinetics of initial cell
attachment while heparan sulfate proteoglycan (HSPG) modulates steady state adhesion strength.
Coating the sensor surface with the positively charged poly-D-lysine (PDL) enhanced the initial
interaction with substratum. In order to relate sensor data to the adhesion of the cells, we performed
independent measures of cell spreading and adhesion strength. The adhesive interactions of human
mammary epithelial cells, MCF-10A, with a fibronectin coated sensor were altered by overexpressing
Her2/Neu oncogene and by blocking integrin function with soluble GRGDS. Correlation of ΔR with
cell spreading and adhesion measurements revealed three phases: adhesion, spreading and structural
reorganization. In the initial adhesion phase, ΔR increases rapidly as the cells bind to the substratum
and began to flatten. The rate of change of ΔR is proportional to the adhesion strength. As the cells
spread beyond their initial projected area, ΔR increased in proportion to the change in area. In the final
phase, as the cells approach their final spread area, further increases in ΔR reflect structural changes,
possibly indicating maturation of cytoskeleton and focal adhesion formation. In order to see the effect
of cell deformability on the initial adhesion, the elastic modulus of spherical cells were evaluated. The
calculation of Young’s moduli showed that oncogene expressing cells were more compliant than
normal cells (1.09kPa±0.36 vs. 2.95kPa±0.34), which was reflected to the initial increase of ∆R. The
real time monitoring capability of this technique with high temporal resolution provides more detailed
information on the kinetics of the different stages of the adhesion process. The analysis of adhesion
properties of normal versus transformed mammary epithelia correlates with changes in integrin
expression, demonstrating the usefulness of TSM sensor measurement system for understanding
adhesion characteristics in real time as it relates to phenotypic variations.
1
CHAPTER 1
BACKGROUNDS
1.1 Cell adhesion mediated by complex intracellular and extracellular events
Cell adhesion has been of particular interest because it plays important roles in the
regulation of cell behavior in wound healing and tissue regeneration, such as the regulation of
growth, differentiation, migration and survival of cells. Cell adhesion is the integrated process
of multiple complex events, such as specific binding of membrane proteins with extracellular
matrix (ECM), intracellular cytoskeleton (CSK) formation and the signal transduction. These
events are strictly controlled by complicated mechanisms and are highly interconnected and
interdependent. This continuous and complex cell adhesion process is driven by ligandreceptor interactions, especially integrin bindings [1]. Heterodimeric transmembrane integrin
receptors recognize ECM ligands, such as fibronectin (FN), vitronectin (VN), laminin (LN)
and collagen. Besides the physical connection, integrin binding relays signals from ECM,
which invoke several subsequential events [2, 3]. Based on integrin binding, cells develop the
intracellular cytoskeleton network, which is the polymeric network of structural filaments
including actin, intermediate filament and microtubule. Especially, the cell shape and structure
are determined by the actin filament formation influenced by signaling by growth factor
receptors and intregrin binding. Actin filament network is physically connected to ECM
proteins through clusters of integrins. During the dynamic cell adhesion process cells actively
modulate cell-ECM interactions and the extracellular signaling by reorganizing the ECM,
rearranging fibrillar components or even secreting the new proteins [4].
1.2 Multi-functional integrin and intrinsic adhesivity of cells
2
As a major family of cell surface receptors, integrins provide physical contacts and
signaling pathways with surrounding environment. Integrins consist of two non-covalently
linked subunits (α and β) and have small C-terminal cytoplasmic domain and large N-terminal
extracellular domain. Both α and β subunits have several homologies (α:18 and β:8), and up to
now 24 combinations have been reported. Integrins (β subunits) are physically connected to
actin filmament with various linker proteins, such as talin, a-actinin and vinculin. Each unique
integrin shows the specificity for the extracellular ligands and distinct functions in cell. Most
integrins recognize tripeptide arg-gly-asp (RGD) sequence in many extracellular proteins [5].
RGD sequence serves as a shared binding site while the specificity is generated by a second
binding site specific for each protein.
Besides the mechanical linkage, integrins have a significant function in signal initiation
and modulation, which is characterized by the bidirectional signaling pathway between ECM
and CK [6, 7]. The ligation of integrins with their ECM proteins induces intracellular
biological processes (Outside-In signaling), such as cytoskeleton formation, phosphorylation
of proteins and gene expression. The intracellular signals regulate the affinity of integrinprotein bindings by modulating conformational changes of integrins and the clustering of
integrins (Inside-out signaling) [8]. The mutual collaboration with other signaling proteins is
the special feature of integrins. Integrins affect the expression and activity of other integrins
and other types of adhesion molecules by cross-talking. The cooperation with receptor
tyrosine kinases (RTKs) amplifies signals and enhances the efficiency of the regulation of
various biological processes. Integrin-ECM interaction activates growth factor receptors and
expedites binding with ligands [9]. For example, the collaboration of erbB2 and α6β4
enhances the activity of phosphatidylinositol 3-kinase (PI3K), which promotes motility and
invasiveness of carcinoma cells [10]. Some integrins can directly regulate growth factors. The
co-clustering of integrins and growth factor receptors induces ligand-independent signaling of
growth factor receptors [11].
3
1.3 Cell spreading determined by integrin binding and actin filament dynamics
Cells continuously regulate their shape in order to adapt themselves to the environment
and to fulfill their task by modulating the dynamic structure of cytoskeleton (including acin
filament, intermediate filament and microtubule). Cell spreading is a cytoskeletal construction
process for membrane extension on the ECM surface, leading to fried-egg shaped morphology.
As cells spread on the ECM substrate, they show characteristic morphology. The stress fibers
cross the cell body, connecting focal adhesions which anchor the cell body to the ECM protein
substrate. In the periphery of the cell body the thin sheet-like lamellipodia and spike-like
filopodia are frequently observed. These structures are continuously reorganized for
maintaining the cell shape and for coping with the external stimuli.
The anchorage site of well spread cells to the substrate can be divided into two
structures, focal adhesion (FA) and focal contact (FC). FA is densely integrated with integrin
bindings and connected with actin stress fiber. The stress fibers generate contractile force
between two FA (The mechanical stress is inevitable for maintaining FA). The periphery of
the cell body, where FCs are frequently observed, has more dynamic in actin filament
formation, especially in the leading edge of lamellipodia. The characteristic lamellipodia
(actin filament meshwork) and filopodia (actin filament bundle) are constructed by
polymerizing actin monomers based on the FC. FC can be transformed into FA or disappear.
The actin polymerization is critically influenced by specific integrin binding and subsequent
signaling. The ligation of integrin activates small GTPases Rho family [12] leading to the
sequential activation of WASP family and then Arp2/3 complex, which regulates overall actin
dynamics for lamellipodial and filopdial protrusions [13, 14].
The initiation of a cascade of events regulating the cell spreading is the integrin binding
with ECM proteins. Indeed, experimentally it was demonstrated that the rate and extent of
spreading is mediated by integrin binding and affected by the density of ECM ligands [15, 16].
Also, ECM condition affects the cell spreading patterns [17].
4
1.4 The phenotype of oncogene expressing cells
Tumor cells are often characterized by being less adherent, more motile and more
compliant than normal cells. In order to accomplish the metastasis, tumor cells have to break
their connections (intercadherin interactions) to neighboring cells and loosen the adhesion
(integrin bindings) on the basement membrane and then, digest, penetrate the basal lamina,
and migrate to reach the blood vessel for gaining the access the circulatory system. These
phenotypic behaviors are closely related to the fact that tumor cells exhibit the different
signaling mechanism initiated by oncogenes. The abnormal activation of oncogenes affects
gene expression and alters the integrin levels on cell surface and actin cytoskeleton network
structures. Levels of integrins of oncogene expressing cells differ according to the cell type
and the transformation system. For example, RSV-transformation of rodent fibroblast line
(rat1) down-regulates α5β1 integrin, while ErbB-2, which is a dominant oncogene in breast
cancer, up-regulates α5β1 integrin. Thus, each oncogene induces characteristic changes of
phenotype in certain environment. Since each integrin has specific function and affinity to the
counterpart ECM protein or other cell membrane proteins, differentiated level of integrins
determines metastatic behavior of tumor cells. The site-specific metastasis is a good example
of targeting the particular organs of tumor cells by means of over expressed integrins. Besides
the role in angiogenesis, αvβ1 integrin promotes the attachment on the blood vessel wall,
which is critical to be arrested under hydrodynamic flow conditions. Overexpression of α6β4,
a laminin receptor, relates with migratory capability of epithelial and carcinoma cells[18].
Also, α6β4 integrin cooperates with ErbB2 in the mammary epithelial tumorigenic process
[19]. Therefore, the evaluation of the integrin-mediated adhesion on specific ECM proteins
provides us useful information of tumorigenic and metastatic phenotype. The comparison
analysis of oncogene expressing cells with normal cells in terms of cell adhesion is helpful for
5
identifying the effect of the specific oncogene on the expression of integrins and for obtaining
direct evidence of cellular behaviors, such as spreading, proliferation and survival.
The integrin-mediated cell adhesion can be modified by various methods. Simply the
cell adhesivity can be reduced by blocking the integrin bindings with ECM proteins using
soluble peptides containing an RGD sequence. The affinity of integrin for soluble ligands is
less than insoluble ECM proteins and the blocking effect does not persist. Also, the integrin
binding with soluble ligand may initiate uncontrolled signaling mechanism. The variation of
cellular adhesivity can be obtained by treating the cell with tumor promoter. 12-Otetradecanoylphorbol-13-acetate (TPA) triggers a series of events leading to the alteration of
cellular shape and the loss of cell adhesivity. TPA activates membrane bound protein kinases
C (PKC), and PKC depolymerizes the actin filaments. However, since it affects various
cellular mechanisms, TPA may not be ideal for cell adhesion study. In contrast, using
oncogene expressing cells for adhesion study has several advantages. The established cell line
by the transfection of active oncogene maintains consistent and stable phenotype in terms of
morphology and expressed integrin levels. The specific integrin or structural components can
be manipulated by gene silencing techniques such as siRNA knock-down.
The receptor tyrosine kinase ErbB-2 (also known as HER2/neu, NeuT is a rat analogue
of ErbB-2) plays important roles in signal transduction leading to the pathogenesis of breast
cancer [20]. The ErbB-2 gene is amplified and ErbB-2 is over-expressed in 25~30% of breast
cancers and has been a major target of breast cancer diagnosis and treatment [21]. The high
level of ErbB-2 is associated with increased disease recurrence and worse prognosis [22].
ErbB-2 has been reported to be closely related to the expression of integrin receptors. The
retroviral transfection of normal cells with pBabe-NeuT induces the genetic modification of
integrin genes and up-regulates α5 integrins. The activation of ErbB-2 led to selective upregulations of α integrin subunits, such as α2, α3, α5 and αV, and the up-regulated α5β1
integrin enhanced long-term cell adhesion on FN [23].
6
1.5 The measurement of intrinsic adhesivity and cell spreading process
For the quantitative evaluation of cell-surface interactions, the assessment of cell
adhesion strength, which indicates the resistance to the applied shear stress on cell body, has
been widely attempted with various methods. In the parallel plate flow assay, a homogenous
flow on the cell surface induces shear stress which is proportional to the flow [24]. Thus, this
assay provides controlled and reliable shear stress, which can not be achieved by the simple
rinsing assay. Centrifugation and spinning disk adhesion assays use the centrifugal force and
the shear stress generated by the rotation, respectively [25, 26]. Whereas, in the centrifugation
device, the cell sample is spun with the rotor in the media, the spinning disk generates shear
flow over the cell layer. Both assays are reported to provide quite quantitative and controllable
operations. However, these techniques have limitations in providing a direct measure of the
intrinsic adhesivity of the cell-surface interaction, especially if used to monitor adhesion
beyond the initial attachment phase. The resistance of cells to detachment by flow depends not
only on the number, distribution and strength of the adhesion bonds formed, but also the
spread area and the surface topography of the cells. As cells spread, resultant drag and torque
on the cell due to flow are dramatically decreased, while the increasing contact area enhances
the ability to resist detachment.
Recently, several attempts have been made in order to quantify the cell spreading and to
determine the effects of property of substrate (e.g. ligand density) on the rate of cell spreading.
Dubin-Thaler et al. monitored the cell spreading and quantified the rate of spreading in nanoscale and tried to describe the cell spreading with two distinct spreading modes [17]. ReinhartKing et al. investigated the changes in cell shape and traction force on polyacrylamide gels, of
which ligand densities were differently manipulated and reported that the rate and extent of
spreading increase with the density of ligands on the substrate [16]. Roberts et al.
7
demonstrated a functionalized surface with self-assembled monolayers (SAMs) presenting
RGD for cell-surface interactions [27].
1.6 Thickness Shear Mode resonator
A TSM sensor is capable of detecting nano-scale changes in mass and in mechanical
properties of interfacial materials on the sensor surface [28]. A TSM sensor, which uses the
piezoelectric effect (The applied voltage generates the mechanical stress and displacement,
vice versa), generates characteristic shear waves penetrating into a contacting media according
to oscillating voltage frequencies (Fig. 1.1A). The vibration of the TSM sensor is affected by
the mass and mechanical properties, such as density and viscosity, of the interfacing material
within the probing depth (Fig. 1.1B). The resonant frequency shift and the scattering
parameter (S21) change have been widely used in describing the behavior of the vibration.
Since the cell adhesion process changes these mechanical properties of the interface between
cells and TSM sensor surface, the analysis of these measurands provides us the information
about the cell-surface interaction during the cell adhesion process. In this study, S21 of 3rd
harmonic frequency (15 MHz) has been measured with a network analyzer (S21 is measured
by sending a signal into the sensor device and detecting what returns as a reflex.) and
converted into the resistance change (ΔR) of the equivalent circuit (See appendix 1). Thus, ΔR
indicates the energy dissipation due to the change of mechanical properties during the cell
adhesion process. This parameter contains distinct features from resonance frequency shifts
for analyzing the cell adhesion process used by others [29-31].
1.7 Objectives
Cell adhesion is a dynamic process mediated by continuous and complex molecular
interactions with an extracellular matrix (ECM). The identification of cell-substrate
interactions and their kinetics is important in understanding the cellular behaviors, such as
8
morphologic change, growth, migration and differentiation of cells. However, the quantitative
and real-time assessment has been limited. Previous studies of cell spreading have focused on
morphological changes assessed by microscopic observations and the image processing. This
type of analysis does not provide direct assessment of adhesivity or mechanical properties of
the cell. Also, a number of techniques for quantifying cell adhesion strength have been
developed to more directly assess adhesivity; however these techniques do not provide real
time analysis of cell-substrate interactions during the spreading process. TSM sensor
measurement is able to provide the quantitative information about the cell-substrate
interaction and its real time progression. More importantly, the functional state of cell
adhesion molecules (CAMs) affected by various factors, such as amount of CAMs, their
activation, and governing signaling mechanism can be assessed.
The main focus of this study was to establish a new experimental and analytical
foundation for assessing cell-substrate interactions and cell adhesion process using TSM
sensor. The specific effects of receptor-mediated adhesion, the glycocalyx, and surface charge
on initial attachment and long term adhesion of cells were investigated. Intrinsic properties
and cell spreading kinetics were assessed by assigning the physical meaning to the
characteristics of sensor response to the cell adhesion process.
Aim 1; Characterize cell-surface interactions in terms of TSM sensor response to the
cell adhesion process.
Hypothesis 1: Interactions of integrin, glycocalyx, and surface charge of cells with the
substrate contribute to different aspect of cell adhesion. These interactions are reflected to the
sensor responses.
Aim 2; Characterize the cellular specific interaction and spreading kinetics and describe
the functional phenotype of oncogene expressing cells.
9
Hypothesis 2: Intrinsic adhesivity and cell spread area change is related to the initial
increasing slope and change of ∆R, respectively. The sensor response distinguishes the
adhesion of oncogene expressing cells from normal cells.
Aim 3; Evaluate the stiffness and deformability and characterize their effect on the
initial attachment.
Hypothesis 3: The alteration of cytoskeleton dynamics induced by the oncogene
signaling changes mechanical properties of cells. Cell stiffness and deformability is related to
the initial change of ∆R.
1
10
A
B
Figure 1.1 The mechanism of the operation of TSM sensor and TSM sensor responses in network
analyzer (B). By the piezoelectric effect, TSM sensor laterally vibrates according to the applied voltage
and this vibration is affected by the mechanical properties, such as density and viscosity, of the
interface that is very close to the sensor surface. Thus, the cell adhesion process, accompanying
mechanical property changes, can be reported by the sensor readings.
11
CHAPTER 2
CELL-SURFACE ADHESIVE INTERACTIONS
2.1 Introduction
Cell adhesion is a complex process involving physical interactions, chemical binding
events, and biological signaling processes. Cellular adhesion plays important roles in the
regulation of cell behavior, such as the control of growth, differentiation during development
and the modulation of cell migration in wound healing, metastasis, and angiogenesis. Cell
adhesion has been one of the important criteria for evaluating the tissue integration of
implanted biomaterials. In particular, quantitative characterization of cell adhesion and its
kinetics provides valuable information for the development of biomaterials. Therefore, a lot of
effort has been made to elucidate dynamic mechanism of cell adhesion. Current techniques for
evaluating the cell spreading and cell adhesion strength are labor intensive and destructive (e.g.
flow detachment assay). Especially, they are not sufficient in providing the detailed kinetics of
adhesion process. Initial attachment and spreading patterns have been studied and various
techniques have been introduced to quantify the cell adhesion strength [17, 26, 32-34].
Morphology and topographical distribution of focal adhesions have been investigated in realtime with confocal microscopy and immuno-staining technique [35, 36].
Recently, the Thickness Shear Mode (TSM) sensor technique has been used to detect
cells adhering to the sensor surface. Since TSM sensor is capable of detecting nano-scale
changes in mass and mechanical properties of interfacial material, it is possible to detect
ligand-receptor binding in real time. This technique has been used in monitoring the cell
adhesion process using resonance frequency shifts [29, 30]. Wegener et al. [37] have shown
that different cell types have their own characteristic frequency changes when they formed
confluent monolayers, and tried to explain frequency shifts with geometrical properties of
12
cells. Janshoff et al. [31] assumed that a monolayer of cells had visocoelastic properties and
tried to estimate viscosity of cell monolayer by comparing impedance measurements with an
electromechanical model. Marx et al. [38] has shown that morphological changes of cells due
to the depolymerization of cytoskeleton caused frequency and resistance shifts. Li et al. [39]
assessed the integrin-mediated cellular interactions with ECM proteins by evaluating the
bandwidth shift.
In this study, our goal was to correlate sensor readings (specifically, the motional
resistance) with adhesion strength. Furthermore, we studied the contributions of the various
molecular components of the interface to the kinetics of cell adhesion. Experiments were
conducted to assess the cell adhesion processes that were affected by inhibition of integrin
binding, degradation of heparan sulfate proteoglycan (HSPG) and surface charge modification.
The real time sensor measurements were characterized and interpreted in terms of distinct
phases of the cell adhesion process.
2.2 Material and methods
2.2.1 Endothelial cell culture.
Bovine Aortic Endothelial Cells (BAECs) were isolated from calf ascending aorta as
previously described [40]. The BAECs were cultured in complete media [Dulbecco’s
modified Eagle’s medium (Mediatech, Inc., Herndon, VA), 100 units/ml penicillin, 100 μg/ml
streptomycin, 250 ng/ml amphotericin B (Sigma Chemical Co., St. Louis, MO), 2 mM/ml Lglutamine and 10% heat-inactivated calf serum (Invitrogen Co., Carlsbad, CA)] in a
humidified, 37ºC incubator with 5% CO2 in air. Passage numbers were between 6 and 14.
Cell suspensions were made by treating the confluent monolayer of BAECs with 0.25%
trypsin for 90 sec, centrifuging at 200 g for 5 min, and resuspending in serum-free media
[Dulbecco’s modified Eagle’s medium (Mediatech, Inc.), 100 units/ml penicillin, 100 μg/ml
13
streptomycin, 250 ng/ml amphotericin B (Sigma Chemical Co.), 2 mM/ml L-glutamine
(Invitrogen Co.)].
2.2.2 TSM sensor device and measurement system.
The sensing device was built on a disk-shaped AT-cut quartz crystal (f0 = 5 MHz) by
attaching a Teflon cylinder of which inner diameter and height were 11 mm and 8 mm
respectively. The 0.33 mm thick crystal was 14 mm in diameter with gold electrodes 7 mm in
diameter. The sensor device was then placed in a humidified, 37ºC incubator with 5% CO2 in
air. The sensor device was connected to a network analyzer (HP 4395A), and a personal
computer was used for controlling the network analyzer and collecting the data. At the
fundamental frequency (5MHz), sensor readings contained fluctuations likely due to
insufficient energy trappings as described by others [39]. Thus, the results reported here are
for the sensor operating at 15 MHz frequency. The TSM sensor response was measured
using Network Analyzer (NA). With our system, tracking the frequency change gave a noisy
signal (see Fig 2.1A and B insets), while the resistance changes at resonant frequency were
very stable and robust. Thus, we used the changes in resistance (∆R) caused by the biological
events at the interface between cells and TSM sensor surface. Resistance changes (∆R) were
acquired every 30 seconds.
2.2.3 Surface coating of TSM sensor.
All experiments were performed in serum-free medium to avoid variability due to
uncontrolled concentration of adhesion molecules and growth factors present in serum. Except
as noted, a gelatin coating of the sensor surface was used as the adhesive substrate. Gelatin
coating was used to provide a uniform surface presenting Arg-Gly-Asp (RGD) peptide
sequence for integrin binding. The TSM sensor was immersed in 0.5% (v/v) gelatin solution
(Sigma Chemical Co.) for 30 min at room temperature. The surplus of gelatin was removed by
aspiration and the surface was rinsed with PBS two times. The thickness of the gelatin coating
was ~10 nm, as assessed by AFM, and produced a negligible change in sensor readings. To
14
create a net positive charge on TSM sensor without gelatin, it was coated with poly-D-lysine
(PDL, mol wt 30,000-70,000) solution (0.1mg/ml in PBS) for 20min. It was rinsed with PBS
twice and allowed to dry overnight.
2.2.4 Soluble Arg-Gly-Asp (RGD) treatment.
The RGD sequence in the extracellular matrix (ECM) is a primary ligand for integrin
receptors. To block integrin binding to gelatin-coated sensor surface, cell suspensions were
treated with soluble RGD peptide (2 mM, Sigma Chemical Co.) for 10 min at room
temperature [37].
2.2.5 Heparinase III treatment.
Heparinase III is an enzyme that digests heparan sulfates selectively from the
membrane surface. The monolayer of BAECs was incubated in Heparinase III (30 mU/ml) in
phenol red free Minimal Essential Media (MEM) [Sigma Chemical Co., 100 units/ml
penicillin, 100 μg/ml streptomycin, 2 mM/ml L-glutamine, and 1% BSA (Sigma Chemical
Co.)] for 3 hrs [41]. After the incubation, the monolayer was rinsed with MEM twice. The cell
suspension was made with same procedure as described above and then was put into the
sensor device.
2.2.6 Experimental Protocol.
Prior to adding the cell suspension, 0.1 ml of serum-free media was placed in the TSM
sensor chamber and allowed to equilibrate to 37ºC. The equilibrium of the temperature was
confirmed by checking the stability of sensor signal. Next, 0.4 ml of cell suspension (37ºC,
3.75×105 cells/ml) was gently pipetted into the chamber for a final concentration of 3×105
cells/ml. The total number of cells per sensor area was approximately the density of a
confluent monolayer of ECs. The initial projected area of the unspread cells was
approximately 15~20% of the sensor surface area. The density of cells was chosen to give the
maximal response without overly constraining their ability to spread.
2.2.7 Optical measurement.
15
Ten sensor chambers were prepared. Five of them were coated with gelatin as
described above and the rest were used without any treatment as bare surface. Cell
suspensions (3×105 cells/ml) of 0.5 ml were placed in each sensor chamber and incubated
(37ºC, 5% CO2). At each time point (10 min, 20 min, 30 min, 40 min and 50 min), following
inoculation, one of the sensors was rinsed to remove the weakly attached and unattached cells
from the surface. Care was taken to make the rinsing procedure consistent between trials.
After removing the cylinder from the sensor, the sensor was held at approximately 45˚ angle
(from horizontal) while 2ml of PBS was slowly pipetted onto the upper edge of the sensor and
allowed to flow down the tilted surface driven by gravity alone. Cells that remained attached
after two rinses were stained with Calcein Green (Invitrogen Co.) to allow visualization on the
opaque sensors. Calcein Green is introduced to the cells in a non-polar ester form that can
diffuse across the plasma membrane. It is then modified by nonspecific esterases into a polar
fluorescent molecule that cannot escape the cell if the membrane is intact. Thus, it also
serves as a viability marker. The cells were imaged using an epifluorescence microscopy, and
the total number of cells in 5 randomly selected microscope fields was counted.
2.3 Results
2.3.1 Characterization of TSM sensor readings.
The time course of the resistance change (∆R) following inoculation was used to
characterize the cell adhesion process (Fig. 1). In the typical response, following an initial
delay time (~10 min), there was a sharp increase in resistance to a new plateau (primary
plateau). Subsequently, there was slower increase in resistance to a new minimum value
(secondary plateau) that either persisted or gradually increased or decreased. The predicted
sedimentation time was approximately 10 min. The changes in adhesion response due to the
various interventions were characterized by changes in the delay time, the slope of the initial
decrease in ∆R, and the size of ∆R at the primary plateau.
16
2.3.2 Correlation of TSM sensor readings with optical cell adhesion measurement.
In parallel experiments, cell suspensions were placed on multiple TSM sensors. For one,
∆R was recorded continuously for 2 hrs. For the others, the experiments were stopped at
various time points after inoculation to evaluate adhesion strength. The TSM sensor surface
was rinsed twice with PBS removing unattached or weakly attached cells.
A detailed comparison of time courses of ∆R shows that the cell adhesion on the bare
sensor surface had a longer delay time before there was any detectable ∆R than that on the
gelatin coated sensor surface (25 vs. 10 min). Furthermore, the slope of the initial increase in
∆R and the size of ∆R at the primary plateau were both smaller than those on gelatin coated
sensor by a factor of 5 (Fig. 2.2A).
The results for cell adhesion on the two surfaces showed a similar pattern as the sensor
readings (Fig. 2.2B). The comparison of time course and degree of cell adhesion between the
bare and gelatin-coated surfaces was consistent with that of sensor readings. The cell adhesion
was detected much greater on the gelatin-coated sensor surface compared to the bare surface.
Similarly, the maximum rate of change in the number of adhered cells and the final number of
adhered cells (at 50 min) were much greater on the gelatin coated sensor (Fig. 2.2B). The
change in the number of adhered cells with time corresponded with the change in sensor
readings (Fig. 2.2C). However, the relationship was slightly different for cells on bare sensor
compared to the gelatin-coated surface. It was noted that there were also differences in the
morphology of the cells that were attached. While cells on bare sensor surface remained round
in shape, cells on gelatin coated surface were well spread (Fig. 2.3).
2.3.3 Integrin binding inhibition with soluble RGD.
Soluble RGD peptides were used for blocking the integrin binding with ECM
molecules. The delay time was similar from both RGD treated and untreated controls.
However, pretreatment with soluble RGD significantly retarded the rate of the initial ∆R (Fig.
2.4A). After the delay time, control cells showed the typical rapid increase to a primary
17
plateau, followed by an additional increase to the secondary plateau (Fig. 2.4B). In contrast,
integrin blocking caused a slower increase to the secondary plateau with no primary plateau.
There was no difference in the secondary plateau and long term ∆R. Fluorescent images of
adherent cells were consistent with the TSM sensor measurement (Fig.2.5). The control
showed more adherent cells at 1 hr than with RGD treatment, while both showed similar cell
numbers at 20 hrs.
2.3.4 TSM sensor coating with PDL.
To evaluate the influence of surface charges on cell adhesion, we coated the sensor
surface with the positively charged PDL. The PDL coating caused a reduced delay time
compared to the control; however, the rate of change in ∆R was similar for both adhesions.
Cells on gelatin layer showed the typical time course of cell adhesion (Fig. 2.6A). Despite the
apparent facilitation of initial adhesion by PDL, the primary plateau ∆R was not as great as
with gelatin, and at longer times the signal returned to baseline values (Fig. 2.6B). Visual
inspection at 20 hrs showed that the cells had become detached (data not shown).
2.3.5 Degradation of HSPGs with heparinase III.
To evaluate the role of the glycocalyx in the adhesion process, we pretreated cells in
culture with Heparinase III. It has been shown that this treatment removes a significant portion
of HSPG from the cell surface [41, 42]. Heparinase III treatment had no effect on the delay
time or the kinetics of the initial increase in ∆R. However, digestion of the HSPG significantly
reduced the steady state ∆R, and this difference persisted for the duration of the experiment
(Fig. 2.7).
2.4 Discussion
We verified the correlation between cell adhesion strength and ∆R reported by the TSM
sensor. Cell adhesion strength was estimated with simple rinsing assay. While this technique
is not quantitative in terms of the detachment forces, care was taken to ensure consistency
18
from trial to trial. There are existing techniques for assessing cell adhesion strength through
the application of more controlled and quantifiable shear flows [26, 32, 34]. However, these
techniques do not provide a direct measure of the intrinsic adhesivity of the cell-surface
interaction, especially if used to monitor adhesion beyond the initial attachment phase. The
resistance of cells to detachment by flow depends not only on the number, distribution and
strength of the adhesion bonds formed, but also the spread area and the surface topography of
the cells. As cells spread, resultant drag and torque on the cell due to flow are dramatically
decreased, while the increasing contact area enhances the ability to resist detachment
(independent of number and strength of adhesion bonds per se) [32]. As the adhesion process
progresses, there is likely to be a distribution of morphologies at a given time point.
The TSM sensor technique interrogates directly the cell-surface interface and therefore
provides different information than the flow detachment assay. Flow detachment assays
provide information about the threshold for detachment (with the caveats on interpretation
listed above), but the sensor readings reflect the contributions of both weakly and strongly
attached cells. While the kinetics of the changes in sensor readings closely match the changes
in adhesion, the changes in ∆R do not scale linearly with the changes in apparent adhesion
strength when comparing adhesion under different conditions. For example, in the initial
phase of adhesion when most of the cells are still only weakly attached, the sensor appears to
have greater sensitivity than the adhesion assay indicated by the higher slope in ∆R v. number
of adherent cells at the early time points (lower left corner of plot in Fig. 2.2C). This
suggests that cells below the detachment strength threshold of the rinsing experiment also
contribute to the ∆R signal. During the spreading process, the strong synergy between
increased contact area and reduced height profile of the cells makes them much more resistant
to detachment independent of the nature of the cell-substrate interaction. Further evidence that
the TSM sensor readings reflect changes in the cell-surface interface rather than adhesion
strength, per se, comes from a comparison of the adhesion on the bare sensor surface and the
19
gelatin-coated surface (Fig. 2.2C). The number of attached cells at 50 min on the bare sensor
was similar to the number attached at 20 min, on gelatin (Fig. 2.2B); however, in the acoustic
measurement, cell adhesion on gelatin surface gave a 3 fold greater ∆R than on the bare
surface (Fig. 2.2A). The majority of the cells on bare surface were rather spherical shape,
while the cells on gelatin were well spread. Differences in relative area of close contact
between the cell membrane and surface [29] and changes in mechanical properties due to the
developing cytoskeleton [43] may both contribute to the sensor readings
The kinetics of cell adhesion depend on the physical, chemical and biological
interactions between the cell and ECM molecules. While the slope and size of the ∆R signal
correlates to the kinetics and strength of the initial adhesion to the substrate, the delay time
suggests an energy barrier to the formation of the initial adhesive contact. Assuming a
constant sedimentation velocity (i.e. neglecting cell-cell interactions), the number of cells on
the surface increases linearly with time from the initial inoculation. The sedimentation process
was completed by approximately 10 min. However, the TSM sensor readings did not detect
the presence of the cells on the sensor surface during this period. In a study of the passive
adsorption of lipid vesicles, which may be considered a model cell membrane without binding
molecules or a glycocalyx. Reimhult et al. [44] reported no delay between the delivery of
vesicles to the sensor surface and the change in sensor readings. Bell et al. [45] developed
theoretically the idea that nonspecific repulsive forces compete with the specific attraction
between cell surface receptors and their extracellular matrix ligands. Our data support this
idea, and the TSM sensor technique presented here could be used to generate quantitative
estimates of the energy barrier.
The initial attachment of cells on the PDL coated TSM sensor further supports the
energy barrier concept. Since the cell membrane is covered with negatively charged
glycocalyx, the electrostatic attraction between cell membrane and positively-charged PDL
surface would tend to lower the energy barrier for cell adhesion. The reduced delay time for
20
adhesion on PDL is consistent with this interpretation. Furthermore, the finding that
electrostatic attraction can facilitate cell-surface interaction is consistent with previous
experimental results [46, 47]. The failure of long-term cell adhesion on PDL in serum-free
media, indicated by the return of ∆R towards the baseline, was due to the absence of ECM
molecules. While in complete media, proteins such as fibronectin and vitronectin are absorbed
onto the surface, the PDL substrate in serum-free media does not provide ECM molecules.
PDL alone does not support integrin binding and focal adhesion formation.
Once adhesion is initiated, the kinetics of the rapid increase in adhesion strength
appears to be mediated by integrin binding between cellular membrane and the substrate.
Using soluble RGD to occupy integrin receptors showed an effect on the initial adhesion
process while degradation of HSPG had no effect on the initial kinetics. This finding is
consistent with known properties of integrins and HSPG. Integrins produce high affinity,
specific binding to ECM ligands while HSPG acts as a low affinity co-receptor that stabilize
and strengthen the integrin binding, facilitating the focal adhesion formation [48, 49]. The
result that heparinase III treatment reduced steady state adhesion strength supports this role for
HSPG. HSPG is also known to regulate the cell signaling mechanisms triggered by binding to
soluble and insoluble extracellular ligands (e.g. growth factor) [50]. However, because our
experiments were performed in serum-free media, this role for HSPG in the adhesion process
was minimized.The long term adhesion in the presence of soluble RGD was not different from
controls. Several explanations for this behavior are possible. First, steady state adhesion in a
spread cell may require fewer integrin bonds than the initial attachment and spreading process.
Second, once the cell is spread on the surface, the integrins and their ECM ligands are in close
apposition while the reaction with soluble RGD will still be transport limited. Third, soluble
RGD may be bound and internalized by the cell, lowering concentration with time. All the
experiments described in this work were performed in the absence of serum. Serum contains a
variety of adhesion molecules and growth factors. The composition of these components
21
present in any given lot of serum is variable. The adsorption of adhesion molecules onto
surfaces is rapid and would, thus, contribute an undefined adhesivity to the sensor surface and
confound our attempts to control and vary surface properties. To evaluate the possible effects
of removing serum, we performed several experiments with serum (data not shown). For
adhesion on gelatin coated sensors, the presence of serum caused a small increase in the
magnitude change. On the bare sensor, serum significantly enhanced the adhesion response.
The presence of adhesion molecules and growth factors appeared to have a synergistic effect
since pre-coating the sensor with serum containing medium produced only a small increase in
adhesion when the cell were seeded in serum-free medium.
2
22
250
200
∆Freq (Hz)
200
150
0
-200
-400
-600
∆R (Ω)
0
60
Time(min)
100
120
Slope
Delay time
∆R
50
A
0
-50
0
20
40
60
Time (min)
80
100
120
250
200
Primary plateau
Secondary plateau
∆R (Ω)
150
100
200
50
∆Freq(Hz)
0
0
B
-200
-400
-600
0
10
Time(hour)
20
-50
0
5
10
Time (hour)
15
20
Figure 2.1 Time course of △R due to the adhesion process of endothelial cells for the initial adhesion
(A) and the steady state adhesion (B). Cell adhesion process can be characterized by changes in the
delay time, the slope of the initial decrease, and the size of
R at plateaus.
23
250
200
On gelatin surface
∆R (Ω)
150
100
50
On bare surface
A
0
-50
0
10
20
30
Time (min)
40
50
60
40
50
30
On gelatin surface
40
30
20
20
10
B
On bare surface
10
0
0
0
10
20
30
Time(min)
40
50
60
Percentage of Attached cells(%)
Density of Attached cells(103/cm2)
60
24
200
160
On gelatin surface
∆R (Ω)
120
80
C
40
On bare surface
0
0
10
20
30
3
2
Density of Attached cells (10 /cm )
40
50
Figure 2.2 Correlation of sensor readings with optical observation. The cell suspensions in serum-free
media were placed on bare and gelatin coated TSM sensors in the incubator (37ºC, 5% CO2). The area
of sensor surface and the number of cells were 0.95 cm2 and 150×103. The sensor readings (△R) were
recorded for 1 hrs (A). For the optical observation, TSM sensors were rinsed with PBS at various time
points during the incubation and adherent cells were counted with the fluorescent microscope. Optical
data are presented with SD. N=5 (B). The correlations of △R with the number of adherent cells were
shown in (C).
25
Figure 2.3 Comparison of the number and morphology of adherent cells on bare and gelatin TSM
sensor after being rinsed with PBS at various time points. The adherent cells were visualized with
epifluorescent microscopy. Size of each picture is 800μm×600μm
26
250
200
∆R (Ω)
150
Control
100
50
Integrin Binding Inhibition
0
A
-50
0
20
40
60
Time (min)
80
100
120
250
200
Control
∆R (Ω)
150
100
Integrin Binding Inhibition
50
B
0
-50
0
5
10
Time (hour)
15
20
Figure 2.4 Influence of integrin binding inhibition with soluble RGD on cell adhesion process. Soluble
RGD peptides (2 mM) were used for blocking integrin binding in order to inhibit the cell adhesion.
RGD treated cell suspension in serum-free media was place on gelatin coated TSM sensors at the same
time with control. The sensor readings (△R) of initial and steady state cell adhesion process were shown
in (A) and (B) respectively.
27
Figure 2.5 Comparison of adherent cells of RGD treated with control at 2 hrs and 20 hrs. TSM sensor
surfaces were rinsed with PBS at each time point and stained: A) Control, 1 hr, B) Control, 20 hr, C)
RGD treated cells, 1 hr, D) RGD treated cells, 20 hr. Size of each picture is 630 μm × 470 μm
28
250
200
∆R (Ω)
150
On gelatin surface
100
50
On PDL surface
A
0
-50
0
20
40
60
Time (min)
80
100
120
250
200
On gelatin surface
∆R (Ω)
150
100
50
On PDL surface
B
0
-50
0
5
10
Time (hour)
15
20
Figure 2.6 Influence of the positively charged surface on cell adhesion process. The TSM sensor
surface was coated with positively charged PDL. The sensor readings (△R) of initial and steady state
cell adhesion process were shown in (A) and (B) respectively.
29
250
200
Control
∆R (Ω)
150
100
Heparinase III treatment
50
0
-50
0
5
10
Time (hour)
15
20
Figure 2.7 Influence of removal of HSPGs from the cell membrane on steady state cell adhesion
process. The monolayer of endothelial cells was treated with Heparinase III, digesting the significant
portion of HSPG from the cell surface.
30
Table 2.1 Evaluation of cell adhesion and its kinetics
31
CHAPTER 3
INTRINSIC ADHESIVITY AND CELL SPREADING
3.1 Introduction
Cell adhesion to extracellular matrix (ECM) proteins is critical for organization of
tissues and plays an essential role in regulating cellular behaviors, such as survival, growth,
differentiation and migration. During cell matrix attachment and spreading, cells undergo
morphologic alterations driven by passive deformation and active reorganization of the
cytoskeleton. Integrin receptors, heterodimeric transmembrane proteins, play a central role in
cell adhesion and spreading. Specific integrin binding provides not only a mechanical linkage
between intracellular actin cytoskeleton and ECM, but also bidirectional transmembrane
signaling pathways [2, 51, 52]. Integrins recognize soluble ligands and insoluble ECM
proteins and their interaction regulates cell responses such as cytoskeleton formation. Ligation
of integrins with their ECM proteins activates the Rho GTPase family (including Rho, Rac
and Cdc42) which is involved in cell spreading and migration [53, 54]. Rho controls stress
fiber formation and the assembly of focal adhesions (FA), and Rac and Cdc42 regulate
lamellipodial protrusion and filopodial extension [55].
There is abundant evidence that cell adhesivity and mechanical properties regulate cell
behaviors such as migration [56, 57]. Adhesivity and deformability also control cell spreading
dynamics, so an analysis of cell spreading dynamics may be useful for characterizing cell
properties that contribute to the functional phenotype of cells. Changes in integrin-mediated
adhesion and signaling are associated with the transformed phenotype [58, 59]. Tumor cells
are characterized by changes in adhesivity to ECM, which may be related to the invasive and
metastatic potential. Alterations in cell-matrix and cell-cell interactions are cell type and
oncogene specific. For example, while the transfection of rodent fibroblast cells with Src and
32
Ras oncogenes reduces the adhesiveness to FN by impairing α5β1 integrins, the activation of
oncogene ErbB2 in breast cancer up-regulates α5β1 integrin and enhances adhesion [23, 60,
61].
Previous studies of cell spreading have focused on morphological changes assessed by
microscopic observations and the image processing [16, 17, 27, 62]. This type of analysis does
not provide direct assessment of adhesivity or mechanical properties of the cell. A number of
techniques for quantifying cell adhesion strength have been developed to more directly assess
adhesivity [24-26]; however these techniques do not provide real time analysis of cellsubstrate interactions during the spreading process.
We have previously used thickness shear mode (TSM) resonators to monitor cell
adhesion in real-time and were able to distinguish qualitatively and semi-quantitatively
adhesion kinetics of endothelial cells as a function of modifications of substrate, cell surface
proteins and integrin blocking [63]. The objectives of the current study are to establish a basis
for using the real time TSM resonator response to cell adhesion and spreading to describe
quantitatively properties of the cell related to its functional phenotype and to demonstrate the
utility of this technique to distinguish malignant epithelial cells from the normal phenotype.
3.2 Material and methods
3.2.1 Cell culture and materials
MCF-10A cells were obtained from ATCC (Manassas, Virginia) and pBabe-NeuT
cDNA, encoding the rat homolog of the ErbB2, was provided by Danielle Carroll (Harvard
Medical School, Boston, MA). Anti-integrin α-5 and actin (C-11) antibodies were obtained
from Santa Cruz Biotechnology, c-neu antibody was obtained from Oncogene Research
(Boston, MA). MCF-10A cells were cultured in DMEM/F-12 media supplemented with 5%
Horse Serum (Invitrogen), 20 ng/ml EGF (Peprotech), 10 μg/ml insulin (Sigma), 100 ng/ml
cholera toxin, 0.5 μg/ml hydrocortisone, 50U/ml penicillin and 50 μg/ml streptomycin
33
(Invitrogen) [64]. All stable cell lines, MCF-10A pBabe (control cell) and MCF-10A pBabeNeuT (NeuT cell), were produced by retroviral infection of MCF-10A cells followed by
treatment with the selectable marker puromycin, as previously described [64].
3.2.2 Cell suspension preparation
For TSM sensor measurement, a cell suspension (7×105 cells/ml) was prepared by
treating control or NeuT cells with 0.25% trypsin, centrifuging, and resuspending the cell
pellets in serum-free media [DMEM/F12 (Invitrogen Co.), 20ng/ml epidermal growth factor
(EGF), 10 μg/ml insulin, 100 ng/ml cholera toxin, 0.5 μg/ml hydrocortisone, 50 units/ml
penicillin and 50 μg/ml streptomycin]. For the inhibition of integrin binding with firbronectin
(FN), MCF-10A pBabe cells were treated with 1mM soluble Gly-Arg-Gly-Asp-Ser (GRGDS;
Sigma Chemical Co.) for 10 min at 37 ºC (GRGDS-treated control cells).
3.2.3 Surface treatment
For coating the surface, both the TSM sensor and the gold coated substrate were
immersed in a 5 μg/ml FN solution (Sigma Chemical Co.) for 1 hour at room temperature.
After the treatment, the solution was aspirated and the surface was rinsed with PBS two times.
3.2.4 TSM sensor measurement
The TSM sensor device and the measurement system have been described previously
(21). Briefly, the sensor device was made by building a chamber, having an inner diameter of
9.2mm and a height of 1.8 mm, on an AT-cut quartz crystal (f0=5MHz, International Crystal
Manufacturing, Oklahoma City, OK). The sensor devices were then placed in a humidified
incubator (37ºC, 5% CO2) and connected to a network analyzer through a custom-designed
micro-wave switch. After temperature equilibrium was established, 130μl of cell suspension
(37ºC, 7×105 cells/ml) was gently pipetted into the chamber. The sensor devices were
operated at the 3rd overtone harmonic frequency (f3=15 MHz), and the resistance changes
(∆R) at the resonance frequency were recorded once every minute. ∆R reports the energy
34
dissipation due to the change of mechanical properties (density and viscosity) during the cell
adhesion process on the sensor surface.
3.2.5 Optical measurement of cell spread area
For optical imaging, the opaque sensor was replaed with a transparent gold substrate
(gold layer thickness: 30nm), prepared by depositing gold onto a circular glass coverslip
(diameter: 15mm) with an e-beam evaporator. At specific time points during the incubation
(37ºC, 5% CO2), images were taken from randomly chosen locations using an inverted
microscope, and then the cells were returned to the incubator. The cell spread area was
calculated with NIH ImageJ program.
3.2.6 Spinning disk adhesion assay
A custom made spinning disk cell detachment device similar to that of Garcia was used
to determine cell adhesion strength[26] (See appendix 2.). The transparent gold coated glass
coverslip (dia: 40mm) was prepared as described above and mounted on the disk (dia: 40mm).
A cell suspension (37ºC, 7×105 cells/ml) was placed on the substrate and incubated (37ºC, 5%
CO2) for 5 min. Then, the disk was installed on the rotating shaft, and the chamber was filled
with PBS (37ºC). The installation time (less than 1 min) was strictly controlled. The rotating
speed was increased over 30 seconds to 2000 rpm (control and NeuT cells) and 1000 rpm
(GRGDS-treated control cells) and then kept constant for 5 minutes before decreasing to zero
over 30 sec. The substrate was transferred to the inverted light microscope, and
photomicrographs were taken at defined positions along the diameter. The shear stress
increases linearly with radial position. The shear stress at which 50% of adherent cells were
removed (τ50%) was used as the measure of adhesion strength.
3.2.7 Western blot
Cell lysates were prepared as previously described[64]. Briefly, cell lysates were
prepared in RIPA buffer (150 mM NaCL, 1% NP-40, 0.5% DOC, 50 mM TrisHCL at pH 8,
0.1% SDS, 10% glycerol, 5 mM EDTA, 20 mM NaF and 1 mM Na3VO4) supplemented with
35
1 μg/ml each of peptatin, leupeptin, aprotinin, and 200 μg/ml PMSF. Lysates were cleared by
centrifugation at 16,000g for 20 min. at 4°C and analyzed by SDS-PAGE and autoradiography.
3.3 Results
3.3.1 Oncogenic regulation of integrin expression
Its been previously shown that the oncogene Her2/Neu can upregulate α5 integrin
expression in mammary epithelial cells[23], We compared the relative amount of α5 integrin
in control MCF-10A cells, a normal human immortalized mammary epithelial cell line, with
cells stably overexpressing oncogenic version of Her2/Neu (NeuT). Our results confirmed that
stable overexpression of the oncogene NeuT induces approximately 2 fold higher protein
expression of α5 integrin compared to normal MCF-10A cells (Fig. 3.1).
3.3.2 Microscopic measurement of cell spread area
Phase contrast photomicrographs were taken in order to quantify the spread area at
specific time points for the comparison with TSM sensor readings (Fig. 3.2). MCF-10A cells
were incubated on FN coated transparent gold substrates, under the same experimental
conditions as the TSM sensor measurements. Most NeuT cells were attached and partially
spread at the 15 minutes and fully spread after 30 minutes. In contrast, many control cells
were still round at 15 minutes, but they continued to spread gradually. GRGDS-treated control
cells showed slower spreading than untreated control (Fig. 3.3A).
3.3.3 Comparison of time course of ΔR with cell area
The change in motional resistance, ΔR, is a measure of the viscous loss at the sensor
surface. The time course of ΔR was compared with the spread area of cells obtained from the
microscopic measurement (Fig. 3.3A). The rate of spreading of MCF-10A cells was increased
as a result of NeuT overexpression, compared to control cells. Conversely, blocking the
specific binding of integrins with soluble GRGDS treatment of control cells decreased the rate
of spreading. In addition, the effects of modulating integrins were also clearly seen in the
36
time-dependent changes in ΔR. The three experimental conditions resulted in qualitative and
quantitative differences in the real time spreading behavior as detected by the TSM sensor.
NeuT cells showed faster initial increase in ΔR compared to control cells. GRGDS-treated
control cells significantly attenuated the ΔR response compared to untreated control cells. The
long-term adhesion profile showed that after the initial sharp increase to a maximum value,
the ΔR for NeuT cells plateaued and even decreased slightly at later time points. In contrast,
the control cells showed gradual increases throughout the experimental period (20 hours) (Fig.
3.3B). Though GRGDS treatment attenuated the response throughout the experimental period,
the profile was similar to the untreated cells, with a continuously increasing signal. Thus,
alteration of integrin expression or function can be qualitative and quantitative measured by
the TSM sensor.
3.3.4 Correlation of TSM sensor readings with cell spread area
Relating the cell area to the changes in ΔR at each time point revealed three distinct
phases in the spreading process (Fig. 3.4). Before the cells spread beyond the projected area of
their spherical shape in suspension, there was an increase in ΔR without a detectable area
change as the cells form initial adhesions and flatten on the surface, but before spreading.
Then there was a period of spreading in which the ΔR was linearly related to the change in
spread area. The same number of cells was used for each condition, so the spread area per cell
is also indicative of the area fraction of the sensor surface occupied by cells. As the cells
approach their maximum spread area, there is a period in which ΔR continues to change at
approximately constant cell area, indicating a change in mechanical properties. The slope of
ΔA/ΔR in the linear region was similar for all three conditions. However, the magnitude of
ΔR for a given area varied owing to the differences in the initial adhesion phase.
3.3.5 Correlation of the initial rate of change of ΔR with τ50%
The integrin mediated adhesivity of cells was investigated with the spinning disk
adhesion assay. MCF-10A cells were incubated on the FN coated substrate for 5 minutes, then
37
exposed to the shear stress generated by the hydrodynamic flow. Photomicrographs of the
adherent cells along one diameter of the substrate were taken after the detachment experiment
(Fig. 3.5). Adhesion strength was quantified in terms of the shear stress at which 50% of
adherent cells became detached, τ50% (Fig. 3.6). τ50% of NeuT cells was higher than control
cells, and GRGDS-treated cells showed the lowest τ50%. The initial (between 5 min and 10
min) rate of change ΔR, was linearly related to the adhesion strength (Fig. 3.6).
3.4 Discussion
We have investigated the real time changes in interfacial structural properties, as
reported by TSM sensor, during the cell adhesion process to determine mechanical and
adhesive properties of cells relevant to their functional phenotype. By independently assessing
spread area and adhesion strength, we were able to relate the characteristics of the sensor
response to the cell adhesion process.
By comparing spread area with sensor readings, we were able to identify three phases
in the spreading process (Table 3.1). After the initial attachment, the cell-substrate contact
area increases as the cell flattens to conform to the sensor surface (Phase I). Next, the cell
spreads beyond the projected area of the unspread spherical cell. During this phase, the ΔR of
the sensor increases linearly with the area (Phase II). After the cells reach their maximum
spread area, there are further changes in ΔR that represent changes in mechanical properties at
the sensor surface (Phase III).
The initial adhesive interaction between the cells and the substrate are driven by the
specific integrin-mediated adhesion. We expected the NeuT transformed cells to have greater
affinity for the FN coated substratum correlating with the enhanced expression of α5β1
integrin[65]. Indeed, these cells showed greater detachment strength in the quantitative cell
adhesion assay. The approximately 2 fold higher expression of α5 in NeuT overexpressing
cells correlates well with the measured increase in adhesion strength. Differences in adhesion
38
strength for normal and transformed MCF-10A cells as well as normal cells blocked with
GRGDS showed a strong correlation with the initial rate of change of ΔR. During this period,
the cell-substrate contact area has not increased beyond the projected area of the unspread
spherical cell, and conventional light microscopy does not allow a direct measure of the
contact area during this phase. The TSM sensor technique reported here provides a method for
monitoring the kinetics of cell adhesion during this phase. Furthermore, the correlation
between the adhesion kinetics reported by the TSM sensor and the adhesion strength provides
more quantitative information on the adhesive interaction than contact area alone.
In Phase II, the cells spread beyond the projected area of the unspread, spherical cell.
The relationship between ΔR and ΔA in phase II is linear with an offset, ΔRo. Even though the
affinity modulation of α5β1 integrin, either by increased expression or by blocking with
soluble GRGDS, induced differences in the size of ΔR at the given spread area, the rate of
increase of ΔR with respect to ΔA was the same for all conditions (Fig. 3.4). Because ΔR is
related to the mechanical properties of the material in contact with the sensor surface, the
linear relationship indicates that the mechanical properties of the cells are constant during this
phase of the spreading process and that the change in ΔR is due to the increase in area fraction
occupied by the cells as they spread. Though we cannot relate the ΔR changes to contact area
during this very early phase of contact, a hypothetical extrapolation of the linear region to zero
contact area has a positive ΔR axis-intercept (ΔRo). The offset in the zero contact area ΔR
may indicate the intrinsic adhesivity of the cell. Consistent with the previous results, ΔRo was
greatest for the NeuT overexpressing cells and least for the GRGDS-treated control cells.
When the spread area reached the maximum, ΔR did not maintain the linear
relationship with ΔA (Phase III). Instead, ΔR continued to increase at approximately constant
cell area indicating a change in mechanical properties. Changes in ΔR during this phase could
represent the formation and maturation of focal adhesions, elaboration of cytoskeleton, or a
combination thereof.
39
The change to the malignant phenotype is characterized by interrelated changes in the
regulation of proliferation and apoptosis, the expression of integrins, and cell motility. The
human mammary epithelial cell model, MCF-10A, used in this study forms normal acinar
structures in 3-D gel cultures, that form hollow duct-like structures and recapitulate many
architectural features of the glandular epithelium in vivo [66]. MCF-10A cells overexpressing
wildtype version of Her2/Neu adopt a premalignant phenotype and disrupts the normal acinar
structure by filling the luminal space [66]. Cells overexpressing the oncogenic version of
Her2/Neu (NeuT) when placed in 3D culture form highly invasive, disorganized and
proliferative structures (S. Caldwell and M. Reginato, unpublished data) with properties
similar to invasive breast cancer in vivo. Transformation can also affect the spreading
behavior because of the increased adhesivity. In addition, Her2/Neu, in concert with
transforming growth factor (TGF)-β, increases the activity of Rac and promotes the motility of
MCF-10A cells [67, 68]. We observed well developed lamellipodia in NeuT cells throughout
the spreading process, which is consistent with this aspect of Her2 overexpression (Fig. 3.2).
Cellular motility is modulated by not only changes in integrin expression, but also other
factors. For example, cell stiffness, cytoskeletal dynamics, and contractile properties all
modulate migratory behavior in addition to cell substrate adhesion [54, 69].
The continuous, real-time sensor response provides not only cell spreading kinetics, but
also intrinsic properties that may help predict migratory and invasive properties of malignant
cells. The characteristic sensor response to the attachment and spreading of the two cell types
reflects differences in adhesive and structural properties relevant to the functional phenotype.
MCF10A pBabe-NeuT cells have rapid spreading with large ΔR, indicating greater adhesion
strength on FN. However there is no progressive increase in ΔR, and even a slight decease,
after spreading is complete, suggesting no further development of cytoskeletal structure or
focal adhesions. MCF 10A pBabe-NeuT cells whose amount of α5 integrins were reduced by
siRNA knock-down assay followed the same profile of untreated NeuT cells, but with smaller
40
size of ΔR (Fig. 3.7A). In contrast, normal cells have less rapid spreading response, but ΔR
continued to increase after cells are fully spread. Simple modulation of adhesivity by blocking
with soluble GRGDS decreased the initial adhesion response in ΔR, but did not alter long
term increase in ΔR, characteristic of the normal response. These characteristic profiles were
also observed in the adhesion of NeuT cells on matrigel, though the values of ΔR were
reduced relative to their responses on FN (Fig 3.7B). Tumorigenic MDA-MB-231 cells on
both FN and matrigel surfaces showed the same profile of NeuT cells on FN (Fig. 3.7C).
3
41
Figure 3.1 MCF-10A cells overexpressing ErbB2 (NeuT) up-regulate integrin α5 expression. Lysates
from cells expressing vector alone (pBabe) or ErbB2 (pBabe-NeuT) were collected and proteins were
analyzed by immunoblotting with antibodies to ErbB2, integrin α5 and actin.
42
43
Figure 3.2 Real time phase contrast photomicrographs of MCF-10A cell spreading on FN surface. The
suspended cells (GRGDS, control and NeuT) were allowed to adhere on FN in serum free media. Even
though GRGDS cells spread slower than control cells, they showed the similar morphology. NeuT cells
showed distinct cell spreading behavior to the rest. While GRGDS and control cells kept their spreading
gradually from the round shape, NeuT cells were quite well attached and showed fast spreading with
well developed lamellipodia through out the spreading process. The size of each photo is 600×450μm2.
Enlarged photos of control and NeuT cells at 15 min incubation were shown in D and E respectively.
350
560
300
480
MCF-10A
pBabe-NeuT
250
400
∆R (Ω)
200
320
MCF-10A pBabe
150
240
100
160
MCF-10A pBabe
(GRGDS treatment)
50
80
A
0
-50
0
20
40
60
Time (min)
80
100
Spread Area (μm2/cell)
44
0
-80
120
350
300
MCF-10A
pBabe-NeuT
250
MCF-10A
pBabe
∆R (Ω)
200
150
MCF-10A pBabe
(GRGDS treatment)
100
50
B
0
-50
0
4
8
12
16
20
Time (hr)
Figure 3.3 A: The comparison of ΔR and ΔA during the MCF-10A cell spreading on FN surface. The
spreading area (NeuT cells: ■, Control cells: ♦, GRGDS-treated control cells: ▲), calculated from the
image processing, were depicted along with the TSM sensor response (Solid lines). This comparison
clear demonstrates that ΔR represents the real time spreading process. A significant difference between
ΔA and ΔR was observed in the early spreading of GRGDS cells, which is due to the overestimation of
real contact area. B: Long-term time course of ΔR due to the MCF-10A cell adhesion on FN surface.
NeuT cells have rapid ΔR increase to the maximum in 2 hours, which may indicate the completion of
spreading. There is no progressive increase in ΔR, and even a slight decease, suggesting no further
development of cytoskeletal structure or focal adhesions. In contrast, normal cells have less rapid
spreading response, but ΔR continued to increase after cells are fully spread.
45
350
300
Spread Area (μm2/cell)
Phase III
250
200
Phase II
150
Phase I
100
50
0
0
50
100
150
200
Δ R (ΔΩ)
Figure 3.4 Correlation of the spread area and TSM sensor reading (ΔR) for GRGDS cells(♦), control
cells(■), NeuT cells(▲). The correlation demonstrates that the cell spreading process consists of three
distinct phases. Phase I represents the initial attachment from sedimentation to flattening and the further
spreading is in phase II, which is characterized by the linear relationship between ΔR and ΔA. The
curve fitted lines from the points in this region have similar slopes and different ΔR axis-intercepts
(ΔRo). When the cell spreading turns into phase III, the linear relationship does not persist. The error
bar represents standard deviation (n=12)
46
Figure 3.5 Photomicrographs of remaining NeuT cells on the substrate after spinning disk detachment.
The distance at which 50% of adherent cells were removed was determined from these sequential
images and the corresponding shear stress (τ50%) was calculated from their linear relationship. Since
hydrodynamic force was designed to remove cells in the stage of very initial attachment. τ50% indicates
the intrinsic adhesivity of the cell. The numbers indicate the distance from the center of the round
substrate. The size of each photo is 600×450μm2.
47
250
MCF-10A
pBabe-NeuT
τ50%(dynes/cm2)
200
150
MCF-10A
pBabe
100
MCF-10A pBabe
(GRGDS treatment)
50
0
0
10
20
30
40
50
60
Initial slope (Ω/min)
Figure 3.6 Correlation of τ50% with the initial slope of ΔR. The initial increasing slope of ΔR was
calculated from the difference of ΔR values at 5 and 10min, which is the similar time frame with the
spinning disk detachment assay for τ50%. The result demonstrates that the initial slope is linearly
proportional to τ50%.
48
350
300
250
MCF 10A pBabe
∆R (Ω)
200
MCF 10A pBabe-NeuT
150
100
50
MCF 10A pBabe-NeuT
α5 knock-down
A
0
-50
0
4
8
12
16
20
Time (hr)
350
300
250
∆Resistance (Ω)
on FN surface
200
on Matrigel surface
150
100
50
B
0
-50
0
4
8
12
Time(hr)
16
20
49
350
300
250
∆Resistance (Ω)
on FN surface
200
150
on Matrigel surface
100
50
C
0
-50
0
4
8
12
16
20
Time(hr)
Figure 3.7 The characteristic sensor response to the attachment and spreading may reflects differences
in adhesive properties relevant to the functional phenotype. A) MCF10A pBabe-NeuT cells have rapid
spreading with large ΔR, indicating greater adhesion strength on FN. Normal cells have less rapid
spreading response, but ΔR continued the gradual increase. α5 integrin knock-down NeuT cells showed
the same profile of NeuT cells, but has reduced size of ΔR. B) The time course of ΔR of NeuT cells on
matrigel surface is similar to that of untreated controls. C) MDA-MB-231 cells followed the same
profiles on both FN and matrigel surface.
50
Table 3.1 Three phases of cell spreading process
51
CHAPTER 4
CELL STIFFNESS AND DEFORMABILITY
4.1 Introduction
In previous decades, mechanical properties of a living cell, which are inherent and/or
externally imposed, have been studied to elucidate cellular functions and states. Mechanical
properties of both adherent and suspended cells are closely related to the cytoskeleton, which
is the polymeric network of structural filaments including actin, intermediate filament and
microtubule [70]. Especially, cortical actin-filaments, which form a dense network close to the
cell membrane, resist the external forces in the front line, determining the cellular stiffness
and deformability [71]. Since the actin-filament network formation is the central indicator for
morphological changes due to various cellular events, such as adhesion, migration and
transformation, the assessment of mechanical properties provides us with substantial
information about the progression of these events. For example, alterations of stiffness and
deformability have been observed in cancer cells and abnormal blood cells, which are
attributed to the reduction of actins and the change of cytoskeleton structural bindings,
respectively [72, 73].
For the measurement of mechanical properties and deformability, many techniques
have been developed [74, 75], such as a micropipette aspiration [76, 77], an optical tweezer
[78], an optical stretcher [73], a microplate compression [79]. Recently, a nano-indentation
using an atomic force microscope (AFM) has been widely used [80, 81] because of the
convenience of the experiment and the simplicity of the theoretical analysis. However, this
nano-indentation assay contains excessive assumptions and only reports regional elastic
properties [82]. Also, it has limitations in providing the deformability which is influenced by
both mechanical properties and cell shape.
52
In this study, the elastic moduli (Young’s moduli) of normal and oncogene expressing
cells were estimated and the effect of the cell stiffness on the cellular initial adhesion was
demonstrated in terms of the TSM sensor measurement. For this, we used a custom made
cantilever with a polystyrene hemisphere attached at the end and deformed a spherical cell
with its flat surface. The deformation of the spherical cell according to the compressive force
was obtained from the force curve and then, Young’s modulus was estimated by applying the
Hertz contact theory. The cell deformation was computer-simulated with a finite element (FE)
analysis and was compared with the experimental data. Also, for reducing the stiffness of
normal cells, the cell suspension was treated with the cytochalasin D (CD), which disrupts the
actin-filament network [83].
4.2 Material and methods
4.2.1 Cell culture and CD treatment
Normal and oncogene (Her2/neu) expressing MCF10A cells were cultured and cell
suspension were prepared as described in 3.2. For the disruption of the actin filaments, CD
stock solution in DMSO was added in normal cell suspension at the final concentration of
0.5μM and incubated for 15 min at 37 ºC.
4.2.2 Atomic Force Microscopy (AFM)
A polystyrene hemisphere (diameter of the flat surface: 40μm) was attached at the end
of the V-shape silicon nitride cantilever (k: 0.12N/m) (Veeco, Santa Barbara, CA) (Fig. 4.1).
The flat surface of the hemisphere was ensured to be parallel to the substrate. The hemisphere
cantilever was calibrated with the commercial standard probe (k: 2.625N/m, Veeco) and its
spring constant was determined to be 0.1828 N/m. The prepared cell suspension was gently
placed on the glass slide installed on the atomic force microscope (Bioscope; Veeco), which
was mounted on the inverted fluorescence microscope (TE2000; Nikon, Melville, N.Y.). In
order to enhance the experimental reproducibility, the center of the hemisphere was placed on
53
the top of the cell and the cantilever was engaged and disengaged periodically (0.5Hz, loading
rate: 4μm/sec) at room temperature. Loading force curve data was stored for the further
analysis. Ten sets (cells) of the experiment were conducted for each sample, i.e. NeuT cells,
control cells and CD-treated cells. The size of a spherical cell was measured with a phase
contrast microscope and determined to be 15μm in diameter. This value was used in both
theoretical and FE analysis.
4.2.3 Theoretical Background and Data analysis
The compressive force (F) and the deformation of the cell (d) can be obtained from the
deflection of the cantilever (δ) and its difference from the movement of the cantilever base (Z),
shown as[80]
F = kδ ,
(4.1)
d = Z −δ ,
(4.2)
where k is the spring constant of the cantilever. Since the compressive force and the
cellular deformation depend on the deflection of the cantilever, the determination of the
deflection due to the contact with the cell, i.e. the contact point from the force curve, is
essential for the overall analysis. In our study, the slope of the deflection in the unit movement
of the cantilever base was calculated and the point that shows the abrupt slope change was
chosen as a contact point in the force curve.
In order to evaluate Young’s modulus of the cell, it was assumed that a spherical cell is
an incompressible, homogeneous, and isotropic elastic solid. Since a spherical cell was
compressed between two rigid parallel plates, one half of the cell body was considered for the
theoretical calculations (Fig. 4.2). Young’s moduli between 2% and 10% deformation were
calculated because the measurement uncertainty under 2% could cause significant
experimental errors (Data not shown) and it was reported that the Hertz contact theory doesn’t
match with the experimental data over 10% deformation [84]. Young’s modulus was
54
calculated by using the Hertz contact theory in which the deformation of an elastic sphere by a
rigid surface can be expressed as [85]
F=
4 E Ro 3 / 2
d ,
3 (1 − υ 2 )
(4.3)
where E is Young’s modulus, Ro is the radius of the cell and ν is Poison’s ratio (ν=0.5).
For the hyperelastic solid analysis, Mooney-Rivlin (MR) solid model has been widely
used for the soft-tissue and its strain energy density function (W) is described [86] as
W = C10 ( I1 − 3) +C 01( I 2 − 3) ,
(4.4)
where C10 and C01 are constants and I1 and I2 are the first and the second invariants,
which are commonly used with
⎫⎪
⎬
I 2 = λ λ + λ λ + λ λ ⎪⎭
I1 = λ12 + λ22 + λ32
2 2
1 2
2 2
2 3
2 2
3 1
(4.5)
where, λs are principal stretch ratios.
Since the cell body was assumed as incompressible (λ1λ2λ3=1) and axisymmetric
(λ2=λ3) , the eq. (4.4) becomes
W = C10 (λ12 + 2λ1−1 ) +C 01(2λ12 + λ1−2 ) ,
(4.6)
and the corresponding stress is
σ 1 = C10 (2λ12 + 2λ1−1 ) +C 01(2λ1 + 2λ1−2 ) .
(4.7)
This provides the expression for the stress in terms of the strain of hyperelastic
materials.
4.2.4 Finite Element (FE) Analysis
The axisymmetric FE models were constructed using the commercial program,
ABAQUS (ver. 6.5, ABAQUS, Inc., Providence, RI). The hemisphere’s flat surface and glass
slide were modeled as rigid bodies, having surface contacts with the cell body (Fig. 4.3). The
average Young’s modulus calculated from the Hertz contact model was assigned to FE model
55
and the reaction forces acting on the rigid surface were obtained in terms of the displacement
of the rigid surface, i.e. the deformation of the cell. The reaction forces were compared with
the AFM experiment data.
For the strain energy density function describing a hyperelastic solid (eq. (4.6)), MR FE
model was made and the reaction force on the flat surface according to the cell deformation
was calculated. The constants (C10 and C01) that have the least mean squared error between
forces of the AFM experiment and the FE simulation were chosen.
4.3 Results
4.3.1 Young’s modulus and deformability of a spherical cell
Young’s modulus of a spherical cell was calculated (Fig. 4.4) by applying the Hertz
contact theory to the relationship between the compressive force and the cell deformation (Fig.
4.5), which was calculated from the force curve (Fig. 4.5 inset). For better understanding,
several representative points from 2% to 10% of cell deformation were selected for depicting
the compressive forces and Young’s moduli. The applied forces gradually increased along
with the deformation of the cells and those of control cells showed bigger values than NeuT
overexpressing cells for the same amount of the deformation. The differences in the calculated
Young’s modulus can be characterized by two features. First, Control cells have bigger
average Young’s modulus than NeuT cells (2.95kPa±0.34 vs. 1.09kPa±0.36), which implies
that the control cells need larger compressive forces than NeuT cells to be deformed by the
same amount. Second, Young’s modulus of control cells showed a gradual increase, making
larger difference with those of NeuT cells, which are similar values throughout the
compression. CD treated cell showed same characteristic behaviors with NeuT cells. Also, the
deformability, defined as the ratio of the cell deformation (d) to the cell radius (Ro) at a given
compressive force, can be assessed from the force-deformation curve (Fig. 4.5). For example,
56
when the 3nN of the compressive force is applied, deformabilities of control and NeuT cells
were 5% and 9%, respectively.
4.3.2 Validation of Hertz contact theory with FE analysis
For the validation of Young’s moduli calculated from the Hertz contact theory, FE
model was constructed and reaction forces were compared with the AFM experiment data (Fig.
4.5). The comparison result demonstrated that FE analysis data are in good agreement with
those of the AFM experiment indicating that the application of the Hertz contact theory
provides reasonable values of Young’s modulus. The control cells showed larger difference
between the experiment and the FE analysis than both NeuT cells and CD treated cells.
4.3.3 Mooney-Rivlin hyperelastic properties of a spherical cell
For the hyperelastic analysis, the force-deformation curve of MR model consistent with
AFM experiment results were obtained from the FE simulation by varying the constants of C10
and C01 (Fig. 4.5). Corresponding constants which have the minimum mean squared error
were -2.7 kPa and 3.0 kPa, respectively. While the stress-strain curve (δ-ε) obtained from the
strain energy density function (W) showed similar values in a small deformation range
(d>6%) with that of Hertz contact theory, the differences between values becomes larger as
the deformation increases (Fig. 4.6).
4.3.4 The effect of cell stiffness on the initial attachment of cells
The reduction of the cell stiffness by disrupting the cytoskeleton with CD treatment
caused the change in the time course of ΔR. The control cells showed typical response
described in Chapter 3, but CD treated cell showed slightly higher values in the initial stage
(<2.5min) than control cells and gradually increased. The adhesion of CD treated cells
maintained smaller ΔR at all later times.
4.4 Discussion
57
AFM, allowing the physical contact with the biological sample under the physiological
condition, has been widely used not only for rastering the surface, but also for estimating
mechanical properties. For mechanical properties, the sample is usually indented with a
pyramid or a sphere AFM tip and Young’s modulus is calculated by applying the Hertz
contact theory which describes the deformation of two elastic contacting spheres. However,
this nano-indentation assay may not be sufficient to evaluate the accurate Young’s modulus
because of several over-assumptions stated by others, such as a nonlinearity of forcedeformation due to the increase of the indenting contact area [82]. Moreover, since the
indentation reports the regional deformation near the surface, the mechanical behavior may
not reflect the property of the entire body. Thus, this cannot provide the direct information
about the deformability. To overcome this limitation, a tipless cantilever was introduced for
compressing a spherical sample, but this also contains problematic issues. The cell sample
tends to be compressed by two non-parallel flat surfaces and the V-shape cantilever may not
cover the deformed surface completely. The experimental method proposed in this study, i.e.
compressing a spherical cell with a hemisphere cantilever, can provide Young’s modulus as
well as deformability while avoiding limitations mentioned above. A wide range of Young’s
moduli of adherent endothelial cell lines (1~10kPa) has been reported from the AFM
indentation work [87-90]. Considering that the suspended spherical cell is softer than the
adherent cell, our result (E: 2.2 ~ 4.0 kPa) seems to be reasonable. However, these values are
higher than those from a micropipette aspiration (0.1~1kPa) [91] and a flexible microplate
(0.3kPa)[79].
AFM experiment results demonstrated that the compressive force showed a gradual
increase in terms of the cell deformation rather than a straight increase (Fig. 4.5). This nonlinearity is attributed to geometrical and material specialties of a round cell. Unlike the typical
compression testing specimen, the contact area of a spherical cell with the flat surface linearly
increases with the deformation and the reaction forces are distributed in the concentric contour
58
pattern. A cell body consists of various proteins, organelles, and filamentous elements.
Especially, cortical actin-filament layer underneath the cell membrane significantly affects on
cellular mechanical properties, which is evidenced by the observation that the disruption of
actin-filaments by CD treatment caused cells to be more compliant and close to the
homogeneity. Theoretically, the total reaction force of the homogeneous elastic sphere
contacting the rigid flat surface is a function of the deformation with the power 3/2 (eq. (4.3))
[84]. However, the compressive forces from the AFM experiment were not well curve-fitted
with the power 3/2, which arises from the fact that a cell shows complex mechanical
properties rather than homogenous elastic solid properties. The comparison of experimental
data with a FE analysis strongly demonstrated that the Hertz contact theory is acceptable to
describe the overall mechanical behavior of the cell under the compression (Fig. 4.5). The
observation that Young’s modulus became larger as the deformation increased leads to the
consideration of the hyperelastic model (Fig. 4.4). The FE simulation showed that the
hyperelastic model can describe the cell deformation better than linear elastic (Hookean) solid
model. The stress-strain curve obtained from the MR hyperelastic strain energy density
function is non-linear. The comparison of stress-strain curves indicates that the stress causing
a unit deformation in MR solid model is greater than that of Hertz contact theory and the
difference become larger as the strain increases. Typically polymers, such as rubber, have
been described well by MR constitutive law. Cross-linked polymer chains allow an easy
deformation at the initial stress, but generate greater resistance to the stress as being stretched
to the cross-linked points. This property can be enhanced by giving more cross-link points,
such as disulfide bonds in vulcanized rubber. The observation that disruption of the crosslinked actin filament network with the CD treatment made the cell lose the non-linearity can
be explained with the same concept. Also, the analysis may indicate that actin filament of
NeuT cells are disrupted by Her2 oncogene signaling, which decreases cellular stiffness.
4
59
Figure 4.1 A polystyrene hemisphere was attached at the end of a silicone nitride cantilever. A spherical
polystyrene bead was half melted on a flat glass slide and the AFM cantilever was engaged on the top
of the formed hemisphere with UV glue, followed by the UV light cure. The spring constant was
determined to be 0.1828N/m using a commercial calibration probe. The bar is 40µm.
60
Figure 4.2 The deformation of one half of a spherical solid compressed by a rigid plate. Hertz contact
theory describes the relationship between the compressive force (F), deformation (d), and elastic
modulus (Young’s modulus) as shown in eq. (4.3). The compressive force is the function of the
deformation with the power 3/2.
61
Figure 4.3 Axisymmetric FE model and its deformation under the compression by two rigid parallel
plate. The average Young’s modulus calculated from the Hertz contact model was assigned to FE
model and the reaction forces acting on the rigid surface wre obtained in terms of the displacement of
the rigid surface.
62
6
5
Young's Modulus, E (kPa)
Control
4
3
CD (0.5μM)
2
NeuT
1
0
0.0
2.0
4.0
6.0
8.0
10.0
12.0
Deformation (d/R, %)
Figure 4.4 Comparison of Young’s moduli calculated with Hertz contact theory (■: Control cells, ◆:
CD treated cells and ▲: NeuT overexpressing cells). For better understanding, several representative
points from 2% to 10% of cell deformation were selected for depicting the Young’s modulus. Control
cells showed bigger averaged values than NeuT cells and while NeuT and CD treated cells maintained
relatively constant values according to the deformation, those of control cells gradually increase. Error
bar indicates the standard deviation (n=10).
63
15.0
150
120
pBabe
Force (F, nN)
Deflection (nm)
12.0
9.0
Control
90
60
CD (0.5μM)
30
NeuT
0
0
500
1000
1500
2000
ΔZ (nm)
6.0
CD (0.5μM)
NeuT
3.0
0.0
0
2
4
6
8
10
12
Deformation (d/R, %)
Figure 4.5 The relationship between the compressive force and the cell deformation from the
experiments (filled symbols and solid lines) and FE model simulations (hollow symbols for Hookean
solid model and ◆ for Mooney-Rivlin solid model). Representative force curves were shown in the inset.
Error bar indicates the standard deviation (n=10).
64
0.8
Stress (kPa)
0.6
0.4
0.2
0.0
0
2
4
6
8
10
12
strain (%)
Figure 4.6 Stress and strain curves of the elastic solid model (solid line) and MR hyperelastic solid
model (dashed line). While solid model has linear stress-strain curve (δ-ε), MR hyperelastic solid model
showed non-linear relationship.
65
150
Control (0.05% DMSO)
120
∆R (Ω)
90
60
30
CD treatment (0.5 μM)
0
-30
0
5
10
15
20
Time (min)
Figure 4.7 The influence of the cell stiffness on the initial attachment of cells. The adhesion of control
cells showed the typical time course of ΔR, but that of CD treated cell showed slightly higher values in
the initial stage (<2.5min), noted by ▼, and gradually increased. This may indicate that CD treated
cells deform faster and generate smaller sensor signals than control cells.
66
CHAPTER 5
CONCLUSIONS AND FUTURE WORK
5.1 Conclusions
This study provides a foundation for using TSM sensors to analyze the adhesion and
spreading of cells in real time. Results of this study showed that the cell sedimentation process
was influenced by electrostatic interactions with the substrate as indicated by change in the
delay time on PDL surface. The initial attachment and spreading process were determined by
integrin binding, and their kinetics and strength could be characterized by the slope and the
size of ∆R at primary plateau, respectively. HSPG contributed the long term adhesion, but did
not affect the initial adhesion kinetics. Independent assessment of cell spread area and
adhesion strength has allowed us to assign physical meaning to the characteristics of the
sensor response in the various phases of the adhesion process. The initial slope of ΔR is
linearly related to the intrinsic adhesivity of cells. In the second phase, ΔR is linearly related
to the spread area of the cell. The comparison of the adhesion of MCF-10A pBabe and pBabeNeuT showed that the activation of ErbB2 produced quantitative differences in cell adhesivity
on FN consistent with the up-regulation of α5β1 integrin. Also, ErbB2 overexpressing cells
showed higher deformability and faster initial attachment. Taken together, these results
demonstrate the utility of the TSM sensor technique for monitoring the kinetics of cell
adhesion in real time. We have shown that the technique is sensitive enough to detect the
effects of specific molecular interventions that can be used to characterize the adhesive state
of a cell or to decipher the molecular constituents of the adhesive interactions with natural or
artificial substrates. The interpretation of the real time changes in ΔR in terms of the intrinsic
adhesivity and the cell spreading process enhance the importance and usefulness of the TSM
67
sensor measurement system in the cell adhesion study, especially, in analyzing the adhesive
characteristics and their effects on the phenotypic variations of cells on specific ECM proteins.
5.2 Future work
The experimental and analytical platform for assessing the cell-surface interactions
described in the current study can be used to investigate several research topics.
5.2.1 Structural changes of cells
The sensor response to the adhesion of various cell lines showed different patterns in
the long terms adhesion, as well as the initial adhesion. Since ΔR reports the energy
dissipation due to the mechanical property changes in the sensor surface, the sensor reading
change, maintaining the constant spread area, indicates structural changes both in the cellsurface and in the cell body. The most possible events that affect the sensor response in the
long term adhesion can be the maturation of cytoskeleton and FA formation. We expect that
their development will decrease the slope (ΔR/ΔA) of phase III. For the correlation with
sensor response, they can be visualized can be quantified either measuring the intensity or/and
the area.
5.2.2. Functional phenotype of tumorigenic cells.
The abnormal activation of oncogene regulates the level of specific integrins and the
corresponding intrinsic adhesivity change determines the overall cell behavior including
spreading kinetics as we have shown in this study. Here, we suggest an investigation
elucidating the relationship between the intrinsic adhesivity and the motility, which is one of
the functional phenotype of tumorigenic cells. The invasive tumorigenic cells are
characterized by the high motility, which is governed by the cell-surface interaction
cytoskeleton dynamics. We hypothesize that the migratory speed of cells are inversely related
68
to the intrinsic adhesivity. The level of integrins can be modulated by various methods, such
as siRNA knock-down technique.
5.2.3 Transformation of cells
The transformation of normal cells into tumorigenic cells accompanies sequential
changes in both cell adhesivity and cell structure. We expected that these changes show the
signature in the time course of ΔR, which reveals characteristics of oncogenes and/or cancer
cell lines. The time course of transformation of cells can be obtained by introducing oncogene
with retrovial infection to normal cells. By analyzing the sensor response to the transformation
process, we might assess not only detail variations in adhesivity and adhesion but also
transformation kinetics.
69
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75
APPENDIX
1. Calculation of the resistance
S 21 = 20 log
100
100 + Z T
100 + Z T = 10
−
S 21
20
×100
Fig. 1.1 The transmission line model of TSM sensor
From the transmission line model (Fig. 1.1), the admittance is
Rm
YT =
Rm
2
⎛
1
+ ⎜⎜ ωLm −
ωC m
⎝
⎞
⎟⎟
⎠
2
⎛
⎞
1
⎜
⎟
ωLm −
⎜
⎟
ωC m
+ i ⎜ ωC o −
2 ⎟
⎛
⎜
1 ⎞ ⎟
2
⎟⎟ ⎟
Rm + ⎜⎜ ωLm −
⎜
ω
C
m
⎝
⎠ ⎠
⎝
Where, Rm = R1 + R2 , Lm = L1 + L2 and C m = C1
At resonance frequency ( ω o )
ωLm −
ZT =
=
1
=0
ωC m
Rm
1 + iω o Rm C o
Rm (1 − iω o Rm Co )
1 + ω o Rm Co
2
2
2
76
ω o 2 Rm 2 Co 2 << 1
100 + Rm (1 − iωo Rm Co ) = k
Where, k = 10
−
S 21
20
×100
R m + 200 R m + ω o R m C o + 100 2 − k 2 = 0
2
2
2
2
− 200 ± 200 2 − 4(1 + ω o Co )(100 2 − k 2 )
2
Rm =
2
2(1 + ωo C o )
2
2
Since ωo Co ≈ 0
2
2
Rm = −100 + k
For Rm >0
1000
600
400
Resistance (Ω)
800
200
0
0
-4
-8
-12
-16
-20
Magnitude (dB)
Fig. 1.2 The relation between Mag (dB) and resistance (Ω). The normal sensor response
region is noted with yellow box.
77
2. TSM sensor measurement.
2.1 Preparation of the sensor device
Chambers were built on a TSM sensor by attaching either Teflon cylinders (ID: 11mm)
or Viton O-rings (ID 10.8mm) on both sides with silicon glue (Fig. 2.1A). For better electric
connections between the TSM sensor and connector, the small amount of silver paint was
applied and dried. A round glass slide was prepared to cover the chamber (Fig. 2.1B). The
TSM sensor was encaged with a transparent plastic box in order to minimize the experimental
error caused by the temperature fluctuation during opening the incubator (Fig. 2.1C). A small
hole was made on the lid of the box (Fig. 2.1D) and TSM sensor was installed right below the
hole. This hole was used for the aspiration and the inoculation of cell suspension.
Fig. 2.1 TSM sensor and sensor device
2.2 Experiment protocol
1) Experiment set-up
78
- The sensor surface is coated with ECM protein (0.5% (v/v) gelatin solution for 30min or
5μg/ml FN solution for 1 hr).
- The surface is rinsed with PBS two times and is immersed with DI water.
- The sensor device (Fig. 2.2A) is placed in the incubator and the sensors are connected to
a network analyzer though a micro-wave switch (Fig. 2.2E). A piece of sponge that
contains water is placed inside of the box.
- The sensors are allowed to be stabilized and the temperature stability in the box is
checked from the sensor response.
2) Cell adhesion measurement. (Experimental steps were shown outside of the incubator for
the demonstration)
- Cell suspension is prepared and the vials are placed in the water bath of the incubator for
10 min.
- DI water is aspirated though the hole (Fig. 2.2B).
- 140μl of cell suspension (7×105 cells/ml) is placed on the sensor (Fig. 2.2C) and the glass
slide is placed on the O-ring (Fig. 2.2D). For the gas exchange the upper part of O-ring
was notched (A nail clipper was used to make notches). For Teflon cylinder sensor
device, 0.5ml of cell suspension (3.75×105 cells/ml) is placed on the sensor. At the
same time, the data acquisition program is operated (Fig. 2.2F).
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Fig. 2.2 Cell adhesion measurement with TSM sensor.
80
3. Cell adhesion assay
3.1 Spinning disk apparatus
The hydrodynamic shear force is applied in controllable manner to adherent cells by
spinning the disk on which cells are allowed to adhere for certain duration.
Fig. 3.1 The spinning disk apparatus and diffusion profile.
The shear stress on the surface is linear proportional to the distance from the center (Fig
3.2) and is simply calculated by
τ = 0.8 ⋅ r (ρμω 3 )
1/ 2
τ = shear stress
μ = fluid viscosity
ω = angular velocity
r = radial dist. from center
ρ = fluid density
(1)
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500
Shear stress (dynes/cm2)
400
300
2000 rpm
200
100
1000 rpm
0
0
5
10
Distance from the center (mm)
15
20
Fig. 3.2 The relationship between the applied shear stress and the distance from the center
3.2 Spinning disk adhesion assay protocol.
1) Preparation of transparent gold coated substrate
- A round glass slide (Dia: 40 mm) is cleaned with 70% alcohol and dried with compressed
air (Fig. 3.3Aa).
- The glass slide is installed in the e-beam evaporator (Fig. 3.3B).
- The surface is coated with Cr (thickness: 5nm), followed by being coated with gold
(thickness: 30nm) (Fig. 3.3Ab). (For the coating procedure, follow the manufacturer’s
manual).
2) Preparation of cell sample on the round glass slide.
- The prepared round glass slide is installed on the spinning disk. The round glass can be
firmly attached on the surface by the suction cup (Fig. 3.3C, D, E, and F).
- A round mask (Dia: 40 mm) that forms rectangle channel is made from an inert rubber
sheet (Fig. 3.3G).
- The mask is placed on the gold coated round glass slide (Fig. 3.3H).
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- The surface in the rectangle channel is coated with FN (5μg/ml) for 1hr at room temp.
- The surface is rinsed with PBS two times.
- The prepared cell suspension (cells/ml) is placed in the channel and the top of the mask is
covered with glass slide (Fig. 3.3I). (In order to make the sample which has well
distributed population of cells, the height of suspension needs to be maintained
constant across the channel).
3) Operation of the spinning disk apparatus
- After incubating the sample for the specific time (e.g. 5min) in a humidified, incubator
with 5% CO2 in air, the spinning disk is installed on the rotating shaft and the chamber
is filled with 37ºC 1X PBS (Fig. 3.3J,K).
- The cover slide and mask are gently removed
- The spinning disk is rotated at specific speed for 5 min with 30 sec increment and 30 sec
decrement. The rotation is controlled with specially designed computer program
(LabView) (Fig. 3.3M,L).
-When the spinning disc stopped, the glass slide is detached and brought to the inverted
microscope. Since the substrate is transparent, the adherent cells can be photographed
with a regular inverted microscope (Fig. 3.3N).
- The distance from the center where the adherent cells are reduced over 50% is calculated.
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84
Fig. 3.3 Spinning disk apparatus and its operation.
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4. Mechanical testing with AFM.
A hemisphere was made by melting a polystyrene microsphere on a glass slide (Fig.
4.1A) and was attached at the end of silicon nitride cantilever (Fig. 4.1B). For the calibration
of the spring constant of the hemisphere cantilever, first we calibrated a regular cantilever
with a commercial standard probe (Fig. 4.1C). Then we used the calibrated probe as a
standard. Cell suspension was placed on the bare glass and the center of hemisphere was
engaged on a single cell (Fig. 4.1D). Then, the force curve was obtained.
Fig. 4.1 Mechanical testing with AFM
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VITA
Soonjin Hong
Education
Ph.D. in Biomedical Engineering, Drexel University, USA 2008
M.S. in Mechanical Engineering, SungKyunKwan University, S. Korea, 1997
B.S. in Mechanical Engineering, SungKyunKwan University, S. Korea, 1995
Employment
Research Engineer (1997 – 2003) Kolon Engineering Co., Ltd., S. Korea
Research Interests
Cell adhesion, Cell-biomaterial interaction, Cell adhesion molecules (CAMs) Integrin-ECM
interaction, Biosensors, Biomaterials, Cellular biomechanics, Oncogene expressing phenotype,
Cell signaling.
Selected Publications.
- Investigation of the intrinsic adhesivity and spreading of normal and oncogene expressing
mammary epithelial cells using thickness shear mode resonator. Hong S et al. (in
preparation)
- Mechanical Property of a Whole Cell Measured by Compressing the Spherical Cells with
Atomic Force Microscopy. Hong S et al. (in preparation)
- Real time monitoring of the effects of Heparan Sulfate Proteoglycan (HSPG) and surface
charge on the cell adhesion process using thickness shear mode (TSM) sensor. Biosens
Bioelectron. 2007 Apr 15;22(9-10):2256-60. Ergezen E et al.
- Real-time analysis of cell-surface adhesive interactions using thickness shear mode resonator.
Biomaterials. 2006 Dec;27(34):5813-20. Hong S et al.
Selected Presentations.
- BAEC Adhesion Analysis Using Thickness Shear Mode Sensor. 2005 Annual Fall Meeting
of the BMES. Sept. 2005 Hong S et al.
- BAEC Adhesion Analysis Using Thickness Shear Mode Sensor. Conf Proc IEEE Eng Med
Biol Soc. 2005;1:1047-50. Hong S et al.
- BAEC sedimentation and adhesion analysis using the QCM. 2004 Annual Fall Meeting of
the BMES. Oct. 2004. Hong S et al.